From 85569fbf9519339935b9c619d6cbafec32871e98 Mon Sep 17 00:00:00 2001 From: jennybc Date: Wed, 10 Jan 2024 19:59:57 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20tidyvers?= =?UTF-8?q?e/readr@49a403384a1bf5597fe8b3ca9e8af067f3c15b85=20=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- dev/articles/column-types.html | 2 +- dev/pkgdown.yml | 2 +- dev/reference/datasource.html | 12 ++++++------ dev/reference/read_delim.html | 2 +- dev/reference/type_convert.html | 8 ++++---- dev/search.json | 2 +- 6 files changed, 14 insertions(+), 14 deletions(-) diff --git a/dev/articles/column-types.html b/dev/articles/column-types.html index 002f23cb..1a0a0e42 100644 --- a/dev/articles/column-types.html +++ b/dev/articles/column-types.html @@ -156,7 +156,7 @@

Legacy behavior#> ) #> Warning: 1 parsing failure. #> row col expected actual file -#> 1001 x 1/0/T/F/TRUE/FALSE 2 '/tmp/RtmpkgAItU/tricky-column-type-guessing-23482ca813cd.csv' +#> 1001 x 1/0/T/F/TRUE/FALSE 2 '/tmp/RtmpZir3ez/tricky-column-type-guessing-2378666c52dc.csv' tail(df) #> # A tibble: 6 × 2 #> x y diff --git a/dev/pkgdown.yml b/dev/pkgdown.yml index fb5a4d2a..a0c6eabf 100644 --- a/dev/pkgdown.yml +++ b/dev/pkgdown.yml @@ -5,7 +5,7 @@ articles: column-types: column-types.html locales: locales.html readr: readr.html -last_built: 2024-01-10T18:04Z +last_built: 2024-01-10T19:59Z urls: reference: https://readr.tidyverse.org/reference article: https://readr.tidyverse.org/articles diff --git a/dev/reference/datasource.html b/dev/reference/datasource.html index f763d77c..612e3f68 100644 --- a/dev/reference/datasource.html +++ b/dev/reference/datasource.html @@ -165,7 +165,7 @@

Examples#> [1] "source_file" "source" datasource(readr_example("mtcars.csv.bz2")) #> [[1]] -#> [1] "/tmp/RtmpASSHEF/file18137126f20" +#> [1] "/tmp/RtmpmWxiqJ/file18471e737c2f" #> #> $skip #> [1] 0 @@ -180,13 +180,13 @@

Examples#> [1] TRUE #> #> $env -#> <environment: 0x55a3f81b5508> +#> <environment: 0x559f72bdbdc8> #> #> attr(,"class") #> [1] "source_file" "source" datasource(readr_example("mtcars.csv.zip")) #> [[1]] -#> [1] "/tmp/RtmpASSHEF/file18135eb33dd6" +#> [1] "/tmp/RtmpmWxiqJ/file184771327078" #> #> $skip #> [1] 0 @@ -201,7 +201,7 @@

Examples#> [1] TRUE #> #> $env -#> <environment: 0x55a3f8020de0> +#> <environment: 0x559f72a30b30> #> #> attr(,"class") #> [1] "source_file" "source" @@ -213,7 +213,7 @@

Examplescon <- rawConnection(charToRaw("abc\n123")) datasource(con) #> [[1]] -#> [1] "/tmp/RtmpASSHEF/file18131eaee8fc" +#> [1] "/tmp/RtmpmWxiqJ/file18471cf0107e" #> #> $skip #> [1] 0 @@ -228,7 +228,7 @@

Examples#> [1] TRUE #> #> $env -#> <environment: 0x55a3f7e9af60> +#> <environment: 0x559f728c37b0> #> #> attr(,"class") #> [1] "source_file" "source" diff --git a/dev/reference/read_delim.html b/dev/reference/read_delim.html index 54fe4e63..a02a79d4 100644 --- a/dev/reference/read_delim.html +++ b/dev/reference/read_delim.html @@ -622,7 +622,7 @@

Examples#> # A tibble: 1 × 5 #> row col expected actual file #> <int> <int> <chr> <chr> <chr> -#> 1 4 1 a double b /tmp/RtmpASSHEF/file1813274ac7e1 +#> 1 4 1 a double b /tmp/RtmpmWxiqJ/file184720ad8f68 # Column names -------------------------------------------------------------- # By default, readr duplicate name repair is noisy diff --git a/dev/reference/type_convert.html b/dev/reference/type_convert.html index e8c995d2..e9cfccc6 100644 --- a/dev/reference/type_convert.html +++ b/dev/reference/type_convert.html @@ -143,8 +143,8 @@

Examples) str(df) #> 'data.frame': 10 obs. of 2 variables: -#> $ x: chr "0.814958464819938" "0.455838981084526" "0.568225354654714" "0.0281991616357118" ... -#> $ y: chr "8" "4" "9" "5" ... +#> $ x: chr "0.616355556994677" "0.304880728013813" "0.48939141863957" "0.148794440552592" ... +#> $ y: chr "2" "3" "9" "1" ... str(type_convert(df)) #> #> ── Column specification ────────────────────────────────────────────────── @@ -153,8 +153,8 @@

Examples#> y = col_double() #> ) #> 'data.frame': 10 obs. of 2 variables: -#> $ x: num 0.815 0.4558 0.5682 0.0282 0.5738 ... -#> $ y: num 8 4 9 5 2 10 3 6 1 7 +#> $ x: num 0.6164 0.3049 0.4894 0.1488 0.0696 ... +#> $ y: num 2 3 9 1 6 8 5 4 7 10 df <- data.frame(x = c("NA", "10"), stringsAsFactors = FALSE) str(type_convert(df)) diff --git a/dev/search.json b/dev/search.json index 59527283..f8a7b3a1 100644 --- a/dev/search.json +++ b/dev/search.json @@ -1 +1 @@ -[{"path":[]},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement codeofconduct@posit.co. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired [Mozilla’s code conduct enforcement ladder][https://github.com/mozilla/inclusion]. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to readr","title":"Contributing to readr","text":"outlines propose change readr. detailed info contributing , tidyverse packages, please see development contributing guide.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"Contributing to readr","text":"can fix typos, spelling mistakes, grammatical errors documentation directly using GitHub web interface, long changes made source file. generally means ’ll need edit roxygen2 comments .R, .Rd file. can find .R file generates .Rd reading comment first line.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"bigger-changes","dir":"","previous_headings":"","what":"Bigger changes","title":"Contributing to readr","text":"want make bigger change, ’s good idea first file issue make sure someone team agrees ’s needed. ’ve found bug, please file issue illustrates bug minimal reprex (also help write unit test, needed).","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"Bigger changes","what":"Pull request process","title":"Contributing to readr","text":"Fork package clone onto computer. haven’t done , recommend using usethis::create_from_github(\"tidyverse/readr\", fork = TRUE). Install development dependencies devtools::install_dev_deps(), make sure package passes R CMD check running devtools::check(). R CMD check doesn’t pass cleanly, ’s good idea ask help continuing. Create Git branch pull request (PR). recommend using usethis::pr_init(\"brief-description--change\"). Make changes, commit git, create PR running usethis::pr_push(), following prompts browser. title PR briefly describe change. body PR contain Fixes #issue-number. user-facing changes, add bullet top NEWS.md (.e. just first header). Follow style described https://style.tidyverse.org/news.html.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"code-style","dir":"","previous_headings":"Bigger changes","what":"Code style","title":"Contributing to readr","text":"New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat unit tests. Contributions test cases included easier accept.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to readr","text":"Please note readr project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://readr.tidyverse.org/dev/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2023 readr authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://readr.tidyverse.org/dev/MAINTENANCE.html","id":"current-state","dir":"","previous_headings":"","what":"Current state","title":"NA","text":"readr somewhat weird state currently. older v1 parsing code base, well calls vroom hood v2. addition still parts, like parse_() functions just use v1 code, currently analogous APIs vroom.","code":""},{"path":"https://readr.tidyverse.org/dev/MAINTENANCE.html","id":"known-outstanding-issues","dir":"","previous_headings":"","what":"Known outstanding issues","title":"NA","text":"Lazy reading causes problems people practice file locking windows. makes technique less effective otherwise unfortunately. v1 parser issues around skipping lines quoting. bunch flux skipped lines counted. known issues v2 parser see vroom MAINTENANCE.md document.","code":""},{"path":"https://readr.tidyverse.org/dev/MAINTENANCE.html","id":"future-directions","dir":"","previous_headings":"","what":"Future directions","title":"NA","text":"think eventually v1 parsing code removed entirely either vroom codebase included directly readr vroom archived, two continue exist readr functions lightweight shim calls vroom.","code":""},{"path":"https://readr.tidyverse.org/dev/SUPPORT.html","id":null,"dir":"","previous_headings":"","what":"Getting help with readr","title":"Getting help with readr","text":"Thanks using readr! filing issue, places explore pieces put together make process smooth possible.","code":""},{"path":"https://readr.tidyverse.org/dev/SUPPORT.html","id":"make-a-reprex","dir":"","previous_headings":"","what":"Make a reprex","title":"Getting help with readr","text":"Start making minimal reproducible example using reprex package. haven’t heard used reprex , ’re treat! Seriously, reprex make R-question-asking endeavors easier (pretty insane ROI five ten minutes ’ll take learn ’s ). additional reprex pointers, check Get help! section tidyverse site.","code":""},{"path":"https://readr.tidyverse.org/dev/SUPPORT.html","id":"where-to-ask","dir":"","previous_headings":"","what":"Where to ask?","title":"Getting help with readr","text":"Armed reprex, next step figure ask. ’s question: start community.rstudio.com, /StackOverflow. people answer questions. ’s bug: ’re right place, file issue. ’re sure: let community help figure ! problem bug feature request, can easily return report . opening new issue, sure search issues pull requests make sure bug hasn’t reported /already fixed development version. default, search pre-populated :issue :open. can edit qualifiers (e.g. :pr, :closed) needed. example, ’d simply remove :open search issues repo, open closed.","code":""},{"path":"https://readr.tidyverse.org/dev/SUPPORT.html","id":"what-happens-next","dir":"","previous_headings":"","what":"What happens next?","title":"Getting help with readr","text":"efficient possible, development tidyverse packages tends bursty, shouldn’t worry don’t get immediate response. Typically don’t look repo sufficient quantity issues accumulates, ’s burst intense activity focus efforts. makes development efficient avoids expensive context switching problems, cost taking longer get back . process makes good reprex particularly important might multiple months initial report start working . can’t reproduce bug, can’t fix !","code":""},{"path":"https://readr.tidyverse.org/dev/articles/column-types.html","id":"automatic-guessing","dir":"Articles","previous_headings":"","what":"Automatic guessing","title":"Column type","text":"don’t explicit specify column types col_types argument, readr attempt guess using simple heuristics. default, inspect 1000 values, evenly spaced first last row. heuristic designed always fast (matter large file ) , experience, good job cases. needed, can request readr use rows supplying guess_max argument. can even supply guess_max = Inf use every row guess column types. might wonder isn’t default. ’s ’s slow: look every column twice, determine type parse value. cases, ’re best supplying col_types .","code":""},{"path":"https://readr.tidyverse.org/dev/articles/column-types.html","id":"legacy-behavior","dir":"Articles","previous_headings":"Automatic guessing","what":"Legacy behavior","title":"Column type","text":"Column type guessing substantially worse first edition readr (meaning, prior v2.0.0), always looked first 1000 rows, application Murphy’s Law, appears many real csv files lots empty values start, followed “excitement” later file. Let’s demonstrate problem slightly tricky file: column x mostly empty, numeric data end, row 1001. first edition parser doesn’t guess right type x 2 becomes NA: specific case, can fix problem marginally increasing guess_max: Unlike second edition, don’t recommend using guess_max = Inf legacy parser, engine pre-allocates large amount memory face uncertainty. means reading guess_max = Inf can extremely slow might even crash R session. Instead specify col_types:","code":"tricky_dat <- tibble::tibble( x = rep(c(\"\", \"2\"), c(1000, 1)), y = \"y\" ) tfile <- tempfile(\"tricky-column-type-guessing-\", fileext = \".csv\") write_csv(tricky_dat, tfile) df <- with_edition(1, read_csv(tfile)) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> x = col_logical(), #> y = col_character() #> ) #> Warning: 1 parsing failure. #> row col expected actual file #> 1001 x 1/0/T/F/TRUE/FALSE 2 '/tmp/RtmpkgAItU/tricky-column-type-guessing-23482ca813cd.csv' tail(df) #> # A tibble: 6 × 2 #> x y #> #> 1 NA y #> 2 NA y #> 3 NA y #> 4 NA y #> 5 NA y #> 6 NA y df <- with_edition(1, read_csv(tfile, guess_max = 1001)) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> x = col_double(), #> y = col_character() #> ) tail(df) #> # A tibble: 6 × 2 #> x y #> #> 1 NA y #> 2 NA y #> 3 NA y #> 4 NA y #> 5 NA y #> 6 2 y df <- with_edition(1, read_csv(tfile, col_types = list(x = col_double()))) tail(df) #> # A tibble: 6 × 2 #> x y #> #> 1 NA y #> 2 NA y #> 3 NA y #> 4 NA y #> 5 NA y #> 6 2 y"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"names-of-months-and-days","dir":"Articles","previous_headings":"Dates and times","what":"Names of months and days","title":"Locales","text":"first argument locale() date_names, controls values used month day names. easiest way specify ISO 639 language code: don’t already know code language, Wikipedia good list. Currently readr 185 languages available. can list date_names_langs(). Specifying locale allows parse dates languages: many languages, ’s common find diacritics stripped can stored ASCII. can tell locale asciify option: Note quality translations variable, especially rarer languages. discover ’re quite right data, can create date_names(). following example creates locale Māori date names:","code":"locale(\"ko\") # Korean #> #> Numbers: 123,456.78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: 일요일 (일), 월요일 (월), 화요일 (화), 수요일 (수), 목요일 (목), #> 금요일 (금), 토요일 (토) #> Months: 1월, 2월, 3월, 4월, 5월, 6월, 7월, 8월, 9월, 10월, 11월, 12월 #> AM/PM: 오전/오후 locale(\"fr\") # French #> #> Numbers: 123,456.78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: dimanche (dim.), lundi (lun.), mardi (mar.), mercredi (mer.), #> jeudi (jeu.), vendredi (ven.), samedi (sam.) #> Months: janvier (janv.), février (févr.), mars (mars), avril (avr.), mai #> (mai), juin (juin), juillet (juil.), août (août), #> septembre (sept.), octobre (oct.), novembre (nov.), #> décembre (déc.) #> AM/PM: AM/PM parse_date(\"1 janvier 2015\", \"%d %B %Y\", locale = locale(\"fr\")) #> [1] \"2015-01-01\" parse_date(\"14 oct. 1979\", \"%d %b %Y\", locale = locale(\"fr\")) #> [1] \"1979-10-14\" parse_date(\"1 août 2015\", \"%d %B %Y\", locale = locale(\"fr\")) #> [1] \"2015-08-01\" parse_date(\"1 aout 2015\", \"%d %B %Y\", locale = locale(\"fr\", asciify = TRUE)) #> [1] \"2015-08-01\" maori <- locale(date_names( day = c(\"Rātapu\", \"Rāhina\", \"Rātū\", \"Rāapa\", \"Rāpare\", \"Rāmere\", \"Rāhoroi\"), mon = c(\"Kohi-tātea\", \"Hui-tanguru\", \"Poutū-te-rangi\", \"Paenga-whāwhā\", \"Haratua\", \"Pipiri\", \"Hōngongoi\", \"Here-turi-kōkā\", \"Mahuru\", \"Whiringa-ā-nuku\", \"Whiringa-ā-rangi\", \"Hakihea\") ))"},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"timezones","dir":"Articles","previous_headings":"Dates and times","what":"Timezones","title":"Locales","text":"Unless otherwise specified, readr assumes times UTC, Universal Coordinated Time (successor GMT almost intents identical). UTC suitable data doesn’t daylight savings - avoids whole class potential problems. data isn’t already UTC, ’ll need supply tz locale: can see complete list time zones OlsonNames(). ’re American, note “EST” Canadian time zone DST. ’s Eastern Standard Time! Instead use: PST/PDT = “US/Pacific” CST/CDT = “US/Central” MST/MDT = “US/Mountain” EST/EDT = “US/Eastern” (Note specific time zones smaller areas don’t follow rules. example, “US/Arizona”, follows mostly follows mountain time, doesn’t daylight savings. ’re dealing historical data, might need even specific zone like “America/North_Dakota/New_Salem” - get accurate time zones.) Note used defaults. individual times timezones ’re using “%Z” (name, e.g. “America/Chicago”) “%z” (offset UTC, e.g. “+0800”), ’ll override defaults. ’s currently good way parse times use US abbreviations. Note date R, changing time zone just changes printed representation - still represents instants time. ’ve loaded non-UTC data, want display UTC, try snippet code:","code":"parse_datetime(\"2001-10-10 20:10\") #> [1] \"2001-10-10 20:10:00 UTC\" parse_datetime(\"2001-10-10 20:10\", locale = locale(tz = \"Pacific/Auckland\")) #> [1] \"2001-10-10 20:10:00 NZDT\" parse_datetime(\"2001-10-10 20:10\", locale = locale(tz = \"Europe/Dublin\")) #> [1] \"2001-10-10 20:10:00 IST\" is_datetime <- sapply(df, inherits, \"POSIXct\") df[is_datetime] <- lapply(df[is_datetime], function(x) { attr(x, \"tzone\") <- \"UTC\" x })"},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"default-formats","dir":"Articles","previous_headings":"Dates and times","what":"Default formats","title":"Locales","text":"Locales also provide default date time formats. date format used guessing column types. default date format %AD, flexible YMD parser (see ?parse_date): ’re American, might want use illogical date system:: time format also used guessing column types. default time format %, flexible HMS parser (see ?parse_time):","code":"str(parse_guess(\"2010-10-10\")) #> Date[1:1], format: \"2010-10-10\" str(parse_guess(\"2010/10/10\")) #> Date[1:1], format: \"2010-10-10\" str(parse_guess(\"01/31/2013\")) #> chr \"01/31/2013\" str(parse_guess(\"01/31/2013\", locale = locale(date_format = \"%m/%d/%Y\"))) #> Date[1:1], format: \"2013-01-31\" str(parse_guess(\"17:55:14\")) #> 'hms' num 17:55:14 #> - attr(*, \"units\")= chr \"secs\" str(parse_guess(\"5:55:14 PM\")) #> 'hms' num 17:55:14 #> - attr(*, \"units\")= chr \"secs\" # Example of a non-standard time str(parse_guess(\"h5m55s14 PM\")) #> chr \"h5m55s14 PM\" str(parse_guess(\"h5m55s14 PM\", locale = locale(time_format = \"h%Hm%Ms%S %p\"))) #> 'hms' num 17:55:14 #> - attr(*, \"units\")= chr \"secs\""},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"character","dir":"Articles","previous_headings":"","what":"Character","title":"Locales","text":"readr functions yield strings encoded UTF-8. encoding likely give good results widest variety settings. default, readr assumes input also UTF-8. less likely case, especially ’re working older datasets. following code illustrates problems encodings: don’t know encoding file uses, try guess_encoding(). ’s 100% perfect (’s fundamentally heuristic), least get pointed right direction:","code":"library(stringi) x <- \"Émigré cause célèbre déjà vu.\\n\" y <- stri_conv(x, \"UTF-8\", \"latin1\") # These strings look like they're identical: x #> [1] \"Émigré cause célèbre déjà vu.\\n\" y #> [1] \"Émigré cause célèbre déjà vu.\\n\" identical(x, y) #> [1] TRUE # But they have different encodings: Encoding(x) #> [1] \"UTF-8\" Encoding(y) #> [1] \"latin1\" # That means while they print the same, their raw (binary) # representation is actually quite different: charToRaw(x) #> [1] c3 89 6d 69 67 72 c3 a9 20 63 61 75 73 65 20 63 c3 a9 6c c3 a8 62 72 #> [24] 65 20 64 c3 a9 6a c3 a0 20 76 75 2e 0a charToRaw(y) #> [1] c9 6d 69 67 72 e9 20 63 61 75 73 65 20 63 e9 6c e8 62 72 65 20 64 e9 #> [24] 6a e0 20 76 75 2e 0a # readr expects strings to be encoded as UTF-8. If they're # not, you'll get weird characters parse_character(x) #> [1] \"Émigré cause célèbre déjà vu.\\n\" parse_character(y) #> [1] \"\\xc9migr\\xe9 cause c\\xe9l\\xe8bre d\\xe9j\\xe0 vu.\\n\" # If you know the encoding, supply it: parse_character(y, locale = locale(encoding = \"latin1\")) #> [1] \"Émigré cause célèbre déjà vu.\\n\" guess_encoding(x) #> # A tibble: 3 × 2 #> encoding confidence #> #> 1 UTF-8 1 #> 2 windows-1250 0.34 #> 3 windows-1252 0.26 guess_encoding(y) #> # A tibble: 2 × 2 #> encoding confidence #> #> 1 ISO-8859-2 0.4 #> 2 ISO-8859-1 0.3 # Note that the first guess produces a valid string, but isn't correct: parse_character(y, locale = locale(encoding = \"ISO-8859-2\")) #> [1] \"Émigré cause célčbre déjŕ vu.\\n\" # But ISO-8859-1 is another name for latin1 parse_character(y, locale = locale(encoding = \"ISO-8859-1\")) #> [1] \"Émigré cause célèbre déjà vu.\\n\""},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"numbers","dir":"Articles","previous_headings":"","what":"Numbers","title":"Locales","text":"countries use decimal point, others use decimal comma. decimal_mark option controls readr uses parsing doubles: Additionally, writing big numbers, might 1,000,000, 1.000.000, 1 000 000, 1'000'000. grouping mark ignored flexible number parser:","code":"parse_double(\"1,23\", locale = locale(decimal_mark = \",\")) #> [1] 1.23 parse_number(\"$1,234.56\") #> [1] 1234.56 parse_number(\"$1.234,56\", locale = locale(decimal_mark = \",\", grouping_mark = \".\") ) #> [1] 1234.56 # readr is smart enough to guess that if you're using , for decimals then # you're probably using . for grouping: parse_number(\"$1.234,56\", locale = locale(decimal_mark = \",\")) #> [1] 1234.56"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"vector-parsers","dir":"Articles","previous_headings":"","what":"Vector parsers","title":"Introduction to readr","text":"’s easiest learn vector parses using parse_ functions. take character vector options. return new vector length old, along attribute describing problems.","code":""},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"atomic-vectors","dir":"Articles","previous_headings":"Vector parsers","what":"Atomic vectors","title":"Introduction to readr","text":"parse_logical(), parse_integer(), parse_double(), parse_character() straightforward parsers produce corresponding atomic vector. default, readr expects . decimal mark , grouping mark. can override default using locale(), described vignette(\"locales\").","code":"parse_integer(c(\"1\", \"2\", \"3\")) #> [1] 1 2 3 parse_double(c(\"1.56\", \"2.34\", \"3.56\")) #> [1] 1.56 2.34 3.56 parse_logical(c(\"true\", \"false\")) #> [1] TRUE FALSE"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"flexible-numeric-parser","dir":"Articles","previous_headings":"Vector parsers","what":"Flexible numeric parser","title":"Introduction to readr","text":"parse_integer() parse_double() strict: input string must single number leading trailing characters. parse_number() flexible: ignores non-numeric prefixes suffixes, knows deal grouping marks. makes suitable reading currencies percentages:","code":"parse_number(c(\"0%\", \"10%\", \"150%\")) #> [1] 0 10 150 parse_number(c(\"$1,234.5\", \"$12.45\")) #> [1] 1234.50 12.45"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"datetimes","dir":"Articles","previous_headings":"Vector parsers","what":"Date/times","title":"Introduction to readr","text":"readr supports three types date/time data: dates: number days since 1970-01-01. times: number seconds since midnight. datetimes: number seconds since midnight 1970-01-01. function takes format argument describes format string. specified, uses default value: parse_datetime() recognises ISO8601 datetimes. parse_date() uses date_format specified locale(). default value %AD uses automatic date parser recognises dates format Y-m-d Y/m/d. parse_time() uses time_format specified locale(). default value %uses automatic time parser recognises times form H:M optionally followed seconds /pm. cases, need supply format, documented parse_datetime():","code":"parse_datetime(\"2010-10-01 21:45\") #> [1] \"2010-10-01 21:45:00 UTC\" parse_date(\"2010-10-01\") #> [1] \"2010-10-01\" parse_time(\"1:00pm\") #> 13:00:00 parse_datetime(\"1 January, 2010\", \"%d %B, %Y\") #> [1] \"2010-01-01 UTC\" parse_datetime(\"02/02/15\", \"%m/%d/%y\") #> [1] \"2015-02-02 UTC\""},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"factors","dir":"Articles","previous_headings":"Vector parsers","what":"Factors","title":"Introduction to readr","text":"reading column known set values, can read directly factor. parse_factor() generate warning value supplied levels.","code":"parse_factor(c(\"a\", \"b\", \"a\"), levels = c(\"a\", \"b\", \"c\")) #> [1] a b a #> Levels: a b c parse_factor(c(\"a\", \"b\", \"d\"), levels = c(\"a\", \"b\", \"c\")) #> Warning: 1 parsing failure. #> row col expected actual #> 3 -- value in level set d #> [1] a b #> attr(,\"problems\") #> # A tibble: 1 × 4 #> row col expected actual #> #> 1 3 NA value in level set d #> Levels: a b c"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"column-specification","dir":"Articles","previous_headings":"","what":"Column specification","title":"Introduction to readr","text":"tedious specify type every column reading file. Instead readr, uses heuristics guess type column. can access results using guess_parser(): guessing policies described documentation individual functions. Guesses fairly strict. example, don’t guess currencies numbers, even though can parse : two parsers never guessed: col_skip() col_factor(). always need supply explicitly. can see specification readr generate column file using spec_csv(), spec_tsv() : bigger files, can often make specification simpler changing default column type using cols_condense() default readr looks first 1000 rows. keeps file parsing speedy, can generate incorrect guesses. example, challenge.csv column types change row 1001, readr guesses wrong types. One way resolve problem increase number rows: Another way manually specify col_type, described .","code":"guess_parser(c(\"a\", \"b\", \"c\")) #> [1] \"character\" guess_parser(c(\"1\", \"2\", \"3\")) #> [1] \"double\" guess_parser(c(\"1,000\", \"2,000\", \"3,000\")) #> [1] \"number\" guess_parser(c(\"2001/10/10\")) #> [1] \"date\" guess_parser(\"$1,234\") #> [1] \"character\" parse_number(\"$1,234\") #> [1] 1234 x <- spec_csv(readr_example(\"challenge.csv\")) mtcars_spec <- spec_csv(readr_example(\"mtcars.csv\")) mtcars_spec #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) cols_condense(mtcars_spec) #> cols( #> .default = col_double() #> ) x <- spec_csv(readr_example(\"challenge.csv\"), guess_max = 1001)"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"rectangular-parsers","dir":"Articles","previous_headings":"","what":"Rectangular parsers","title":"Introduction to readr","text":"readr comes five parsers rectangular file formats: read_csv() read_csv2() csv files read_tsv() tabs separated files read_fwf() fixed-width files read_log() web log files functions firsts calls spec_xxx() (described ), parses file according column specification: rectangular parsing functions almost always succeed; ’ll fail format severely messed . Instead, readr generate data frame problems. first printed , can access problems(): ’ve already seen one way handling bad guesses: increasing number rows used guess type column. Another approach manually supply column specification.","code":"df1 <- read_csv(readr_example(\"challenge.csv\")) #> Rows: 2000 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): x #> date (1): y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. problems(df1) #> # A tibble: 0 × 5 #> # ℹ 5 variables: row , col , expected , actual , #> # file df2 <- read_csv(readr_example(\"challenge.csv\"), guess_max = 1001) #> Rows: 2000 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): x #> date (1): y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message."},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"overriding-the-defaults","dir":"Articles","previous_headings":"Rectangular parsers","what":"Overriding the defaults","title":"Introduction to readr","text":"previous examples, may noticed readr printed column specification used parse file: can also access fact using spec(): (also allows access full column specification ’re reading wide file. default, readr print specification first 20 columns.) want manually specify column types, can start copying pasting code, tweaking fix parsing problems. general, ’s good practice supply explicit column specification. work, ensures get warnings data changes unexpected ways. really strict, can use stop_for_problems(df3). throw error parsing problems, forcing fix problems proceeding analysis.","code":"#> Parsed with column specification: #> cols( #> x = col_integer(), #> y = col_character() #> ) spec(df1) #> cols( #> x = col_double(), #> y = col_date(format = \"\") #> ) spec(df2) #> cols( #> x = col_double(), #> y = col_date(format = \"\") #> ) df3 <- read_csv( readr_example(\"challenge.csv\"), col_types = list( x = col_double(), y = col_date(format = \"\") ) )"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"available-column-specifications","dir":"Articles","previous_headings":"Rectangular parsers","what":"Available column specifications","title":"Introduction to readr","text":"available specifications : (string abbreviations brackets) col_logical() [l], containing T, F, TRUE FALSE. col_integer() [], integers. col_double() [d], doubles. col_character() [c], everything else. col_factor(levels, ordered) [f], fixed set values. col_date(format = \"\") [D]: locale’s date_format. col_time(format = \"\") [t]: locale’s time_format. col_datetime(format = \"\") [T]: ISO8601 date times col_number() [n], numbers containing grouping_mark col_skip() [_, -], don’t import column. col_guess() [?], parse using “best” type based input. Use col_types argument override default choices. two ways use : string: \"dc__d\": read first column double, second character, skip next two read last column double. (’s way use form types take additional parameters.) (named) list col objects: , abbreviations: omitted columns parsed automatically, previous call lead result : can also set default type used instead relying automatic detection columns don’t specify: want read specified columns, use cols_only():","code":"read_csv(\"iris.csv\", col_types = list( Sepal.Length = col_double(), Sepal.Width = col_double(), Petal.Length = col_double(), Petal.Width = col_double(), Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\")) )) read_csv(\"iris.csv\", col_types = list( Sepal.Length = \"d\", Sepal.Width = \"d\", Petal.Length = \"d\", Petal.Width = \"d\", Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\")) )) read_csv(\"iris.csv\", col_types = list( Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\"))) ) read_csv(\"iris.csv\", col_types = list( Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\")), .default = col_double()) ) read_csv(\"iris.csv\", col_types = cols_only( Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\"))) )"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"output","dir":"Articles","previous_headings":"Rectangular parsers","what":"Output","title":"Introduction to readr","text":"output functions tibble. Note characters never automatically converted factors (.e. stringsAsFactors = FALSE) column names left , munged valid R identifiers (.e. check.names = TRUE). Row names never set. Attributes store column specification (spec()) parsing problems (problems()).","code":""},{"path":"https://readr.tidyverse.org/dev/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Hadley Wickham. Author. Jim Hester. Author. Romain Francois. Contributor. Jennifer Bryan. Author, maintainer. Shelby Bearrows. Contributor. . Copyright holder, funder. https://github.com/mandreyel/. Copyright holder. mio library Jukka Jylänki. Contributor, copyright holder. grisu3 implementation Mikkel Jørgensen. Contributor, copyright holder. grisu3 implementation","code":""},{"path":"https://readr.tidyverse.org/dev/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Wickham H, Hester J, Bryan J (2024). readr: Read Rectangular Text Data. R package version 2.1.4.9000, https://github.com/tidyverse/readr, https://readr.tidyverse.org.","code":"@Manual{, title = {readr: Read Rectangular Text Data}, author = {Hadley Wickham and Jim Hester and Jennifer Bryan}, year = {2024}, note = {R package version 2.1.4.9000, https://github.com/tidyverse/readr}, url = {https://readr.tidyverse.org}, }"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Read Rectangular Text Data","text":"goal readr provide fast friendly way read rectangular data delimited files, comma-separated values (CSV) tab-separated values (TSV). designed parse many types data found wild, providing informative problem report parsing leads unexpected results. new readr, best place start data import chapter R Data Science.","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Read Rectangular Text Data","text":"","code":"# The easiest way to get readr is to install the whole tidyverse: install.packages(\"tidyverse\") # Alternatively, install just readr: install.packages(\"readr\") # Or you can install the development version from GitHub: # install.packages(\"pak\") pak::pak(\"tidyverse/readr\")"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Read Rectangular Text Data","text":"readr part core tidyverse, can load : course, can also load readr individual package: read rectangular dataset readr, combine two pieces: function parses lines file individual fields column specification. readr supports following file formats read_*() functions: read_csv(): comma-separated values (CSV) read_tsv(): tab-separated values (TSV) read_csv2(): semicolon-separated values , decimal mark read_delim(): delimited files (CSV TSV important special cases) read_fwf(): fixed-width files read_table(): whitespace-separated files read_log(): web log files column specification describes column converted character vector specific data type (e.g. character, numeric, datetime, etc.). absence column specification, readr guess column types data. vignette(\"column-types\") gives detail readr guesses column types. Column type guessing handy, especially data exploration, ’s important remember just guesses. data analysis project matures past exploratory phase, best strategy provide explicit column types. following example loads sample file bundled readr guesses column types: Note readr prints column types – guessed column types, case. useful allows check columns read expect. haven’t, means need provide column specification. sounds like lot trouble, luckily readr affords nice workflow . Use spec() retrieve (guessed) column specification initial effort. Now can copy, paste, tweak , create explicit readr call expresses desired column types. express sex factor levels rooster hen, order, eggs_laid integer. vignette(\"readr\") gives expanded introduction readr.","code":"library(tidyverse) #> ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── #> ✔ dplyr 1.1.4 ✔ readr 2.1.4.9000 #> ✔ forcats 1.0.0 ✔ stringr 1.5.1 #> ✔ ggplot2 3.4.3 ✔ tibble 3.2.1 #> ✔ lubridate 1.9.3 ✔ tidyr 1.3.0 #> ✔ purrr 1.0.2 #> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── #> ✖ dplyr::filter() masks stats::filter() #> ✖ dplyr::lag() masks stats::lag() #> ℹ Use the conflicted package () to force all conflicts to become errors library(readr) (chickens <- read_csv(readr_example(\"chickens.csv\"))) #> Rows: 5 Columns: 4 #> ── Column specification ──────────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (3): chicken, sex, motto #> dbl (1): eggs_laid #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 4 #> chicken sex eggs_laid motto #> #> 1 Foghorn Leghorn rooster 0 That's a joke, ah say, that's a jok… #> 2 Chicken Little hen 3 The sky is falling! #> 3 Ginger hen 12 Listen. We'll either die free chick… #> 4 Camilla the Chicken hen 7 Bawk, buck, ba-gawk. #> 5 Ernie The Giant Chicken rooster 0 Put Captain Solo in the cargo hold. spec(chickens) #> cols( #> chicken = col_character(), #> sex = col_character(), #> eggs_laid = col_double(), #> motto = col_character() #> ) chickens <- read_csv( readr_example(\"chickens.csv\"), col_types = cols( chicken = col_character(), sex = col_factor(levels = c(\"rooster\", \"hen\")), eggs_laid = col_integer(), motto = col_character() ) ) chickens #> # A tibble: 5 × 4 #> chicken sex eggs_laid motto #> #> 1 Foghorn Leghorn rooster 0 That's a joke, ah say, that's a jok… #> 2 Chicken Little hen 3 The sky is falling! #> 3 Ginger hen 12 Listen. We'll either die free chick… #> 4 Camilla the Chicken hen 7 Bawk, buck, ba-gawk. #> 5 Ernie The Giant Chicken rooster 0 Put Captain Solo in the cargo hold."},{"path":"https://readr.tidyverse.org/dev/index.html","id":"editions","dir":"","previous_headings":"","what":"Editions","title":"Read Rectangular Text Data","text":"readr got new parsing engine version 2.0.0 (released July 2021). -called second edition, readr calls vroom::vroom(), default. parsing engine readr versions prior 2.0.0 now called first edition. ’re using readr >= 2.0.0, can still access first edition parsing via functions with_edition(1, ...) local_edition(1). , obviously, ’re using readr < 2.0.0, get first edition parsing, definition, ’s . continue support first edition number releases, overall goal make second edition uniformly better first. Therefore plan eventually deprecate remove first edition code. New code actively-maintained code use second edition. workarounds with_edition(1, ...) local_edition(1) offered pragmatic way patch legacy code temporary solution infelicities identified second edition matures.","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"alternatives","dir":"","previous_headings":"","what":"Alternatives","title":"Read Rectangular Text Data","text":"two main alternatives readr: base R data.table’s fread(). important differences discussed .","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"base-r","dir":"","previous_headings":"Alternatives","what":"Base R","title":"Read Rectangular Text Data","text":"Compared corresponding base functions, readr functions: Use consistent naming scheme parameters (e.g. col_names col_types header colClasses). generally much faster (10x-100x) depending dataset. Leave strings default, automatically parse common date/time formats. helpful progress bar loading going take . functions work exactly way regardless current locale. override US-centric defaults, use locale().","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"datatable-and-fread","dir":"","previous_headings":"Alternatives","what":"data.table and fread()","title":"Read Rectangular Text Data","text":"data.table function similar read_csv() called fread(). Compared fread(), readr functions: sometimes slower, particularly numeric heavy data. Can automatically guess parameters, basically encourage explicit specification , e.g., delimiter, skipped rows, header row. Follow tidyverse-wide conventions, returning tibble, standard approach column name repair, common mini-language column selection.","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"acknowledgements","dir":"","previous_headings":"","what":"Acknowledgements","title":"Read Rectangular Text Data","text":"Thanks : Joe Cheng showing beauty deterministic finite automata parsing, teaching write tokenizer. JJ Allaire helping come design makes copies, easy extend. Dirk Eddelbuettel coming name!","code":""},{"path":"https://readr.tidyverse.org/dev/reference/Tokenizers.html","id":null,"dir":"Reference","previous_headings":"","what":"Tokenizers. — Tokenizers","title":"Tokenizers. — Tokenizers","text":"Explicitly create tokenizer objects. Usually call function, instead use one use friendly wrappers like read_csv().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/Tokenizers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tokenizers. — Tokenizers","text":"","code":"tokenizer_delim( delim, quote = \"\\\"\", na = \"NA\", quoted_na = TRUE, comment = \"\", trim_ws = TRUE, escape_double = TRUE, escape_backslash = FALSE, skip_empty_rows = TRUE ) tokenizer_csv( na = \"NA\", quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip_empty_rows = TRUE ) tokenizer_tsv( na = \"NA\", quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip_empty_rows = TRUE ) tokenizer_line(na = character(), skip_empty_rows = TRUE) tokenizer_log(trim_ws) tokenizer_fwf( begin, end, na = \"NA\", comment = \"\", trim_ws = TRUE, skip_empty_rows = TRUE ) tokenizer_ws(na = \"NA\", comment = \"\", skip_empty_rows = TRUE)"},{"path":"https://readr.tidyverse.org/dev/reference/Tokenizers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tokenizers. — Tokenizers","text":"delim Single character used separate fields within record. quote Single character used quote strings. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. begin, end Begin end offsets file. C++ offsets first column column zero, ranges [begin, end) (.e inclusive-exclusive).","code":""},{"path":"https://readr.tidyverse.org/dev/reference/Tokenizers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tokenizers. — Tokenizers","text":"","code":"tokenizer_csv() #> $delim #> [1] \",\" #> #> $quote #> [1] \"\\\"\" #> #> $na #> [1] \"NA\" #> #> $quoted_na #> [1] TRUE #> #> $comment #> [1] \"\" #> #> $trim_ws #> [1] TRUE #> #> $escape_double #> [1] TRUE #> #> $escape_backslash #> [1] FALSE #> #> $skip_empty_rows #> [1] TRUE #> #> attr(,\"class\") #> [1] \"tokenizer_delim\""},{"path":"https://readr.tidyverse.org/dev/reference/as.col_spec.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a column specification — as.col_spec","title":"Generate a column specification — as.col_spec","text":"useful generating specification using short form","code":""},{"path":"https://readr.tidyverse.org/dev/reference/as.col_spec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a column specification — as.col_spec","text":"","code":"as.col_spec(x)"},{"path":"https://readr.tidyverse.org/dev/reference/as.col_spec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a column specification — as.col_spec","text":"x Input object","code":""},{"path":"https://readr.tidyverse.org/dev/reference/as.col_spec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a column specification — as.col_spec","text":"","code":"as.col_spec(\"cccnnn\") #> cols( #> col_character(), #> col_character(), #> col_character(), #> col_number(), #> col_number(), #> col_number() #> )"},{"path":"https://readr.tidyverse.org/dev/reference/callback.html","id":null,"dir":"Reference","previous_headings":"","what":"Callback classes — callback","title":"Callback classes — callback","text":"classes used define callback behaviors.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/callback.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Callback classes — callback","text":"ChunkCallback Callback interface definition, callback functions inherit class. SideEffectChunkCallback Callback function used side effects, results returned. DataFrameCallback Callback function combines result together end. AccumulateCallBack Callback function accumulates single result. Requires parameter acc specify initial value accumulator. parameter acc NULL default.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/callback.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Callback classes — callback","text":"","code":"## If given a regular function it is converted to a SideEffectChunkCallback # view structure of each chunk read_lines_chunked(readr_example(\"mtcars.csv\"), str, chunk_size = 5) #> chr [1:5] \"\\\"mpg\\\",\\\"cyl\\\",\\\"disp\\\",\\\"hp\\\",\\\"drat\\\",\\\"wt\\\",\\\"qsec\\\",\\\"vs\\\",\\\"am\\\",\\\"gear\\\",\\\"carb\\\"\" ... #> chr [1:5] \"18.7,8,360,175,3.15,3.44,17.02,0,0,3,2\" ... #> chr [1:5] \"19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4\" ... #> chr [1:5] \"10.4,8,472,205,2.93,5.25,17.98,0,0,3,4\" ... #> chr [1:5] \"33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1\" ... #> chr [1:5] \"19.2,8,400,175,3.08,3.845,17.05,0,0,3,2\" ... #> chr [1:3] \"19.7,6,145,175,3.62,2.77,15.5,0,1,5,6\" ... #> NULL # Print starting line of each chunk f <- function(x, pos) print(pos) read_lines_chunked(readr_example(\"mtcars.csv\"), SideEffectChunkCallback$new(f), chunk_size = 5) #> [1] 1 #> [1] 6 #> [1] 11 #> [1] 16 #> [1] 21 #> [1] 26 #> [1] 31 #> NULL # If combined results are desired you can use the DataFrameCallback # Cars with 3 gears f <- function(x, pos) subset(x, gear == 3) read_csv_chunked(readr_example(\"mtcars.csv\"), DataFrameCallback$new(f), chunk_size = 5) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> # A tibble: 15 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 2 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 3 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 4 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 5 16.4 8 276. 180 3.07 4.07 17.4 0 0 3 3 #> 6 17.3 8 276. 180 3.07 3.73 17.6 0 0 3 3 #> 7 15.2 8 276. 180 3.07 3.78 18 0 0 3 3 #> 8 10.4 8 472 205 2.93 5.25 18.0 0 0 3 4 #> 9 10.4 8 460 215 3 5.42 17.8 0 0 3 4 #> 10 14.7 8 440 230 3.23 5.34 17.4 0 0 3 4 #> 11 21.5 4 120. 97 3.7 2.46 20.0 1 0 3 1 #> 12 15.5 8 318 150 2.76 3.52 16.9 0 0 3 2 #> 13 15.2 8 304 150 3.15 3.44 17.3 0 0 3 2 #> 14 13.3 8 350 245 3.73 3.84 15.4 0 0 3 4 #> 15 19.2 8 400 175 3.08 3.84 17.0 0 0 3 2 # The ListCallback can be used for more flexible output f <- function(x, pos) x$mpg[x$hp > 100] read_csv_chunked(readr_example(\"mtcars.csv\"), ListCallback$new(f), chunk_size = 5) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> [[1]] #> [1] 21.0 21.0 21.4 18.7 #> #> [[2]] #> [1] 18.1 14.3 19.2 #> #> [[3]] #> [1] 17.8 16.4 17.3 15.2 10.4 #> #> [[4]] #> [1] 10.4 14.7 #> #> [[5]] #> [1] 15.5 15.2 13.3 19.2 #> #> [[6]] #> [1] 30.4 15.8 19.7 #> #> [[7]] #> [1] 15.0 21.4 #> # The AccumulateCallback accumulates results from each chunk f <- function(x, pos, acc) sum(x$mpg) + acc read_csv_chunked(readr_example(\"mtcars.csv\"), AccumulateCallback$new(f, acc = 0), chunk_size = 5) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> [1] 642.9"},{"path":"https://readr.tidyverse.org/dev/reference/clipboard.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns values from the clipboard — clipboard","title":"Returns values from the clipboard — clipboard","text":"useful read_delim() functions read clipboard.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/clipboard.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns values from the clipboard — clipboard","text":"","code":"clipboard()"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/col_skip.html","id":null,"dir":"Reference","previous_headings":"","what":"Skip a column — col_skip","title":"Skip a column — col_skip","text":"Use function ignore column reading file. skip columns otherwise specified, use cols_only().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/col_skip.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Skip a column — col_skip","text":"","code":"col_skip()"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":null,"dir":"Reference","previous_headings":"","what":"Create column specification — cols","title":"Create column specification — cols","text":"cols() includes columns input data, guessing column types default. cols_only() includes columns explicitly specify, skipping rest. general can substitute list() cols() without changing behavior.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create column specification — cols","text":"","code":"cols(..., .default = col_guess()) cols_only(...)"},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create column specification — cols","text":"... Either column objects created col_*(), abbreviated character names (described col_types argument read_delim()). overriding columns, best refer columns name. named, column types must match column names exactly. .default named columns explicitly overridden ... read column type.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create column specification — cols","text":"available specifications : (string abbreviations brackets) col_logical() [l], containing T, F, TRUE FALSE. col_integer() [], integers. col_double() [d], doubles. col_character() [c], everything else. col_factor(levels, ordered) [f], fixed set values. col_date(format = \"\") [D]: locale's date_format. col_time(format = \"\") [t]: locale's time_format. col_datetime(format = \"\") [T]: ISO8601 date times col_number() [n], numbers containing grouping_mark col_skip() [_, -], import column. col_guess() [?], parse using \"best\" type based input.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create column specification — cols","text":"","code":"cols(a = col_integer()) #> cols( #> a = col_integer() #> ) cols_only(a = col_integer()) #> cols_only( #> a = col_integer() #> ) # You can also use the standard abbreviations cols(a = \"i\") #> cols( #> a = col_integer() #> ) cols(a = \"i\", b = \"d\", c = \"_\") #> cols( #> a = col_integer(), #> b = col_double(), #> c = col_skip() #> ) # You can also use multiple sets of column definitions by combining # them like so: t1 <- cols( column_one = col_integer(), column_two = col_number() ) t2 <- cols( column_three = col_character() ) t3 <- t1 t3$cols <- c(t1$cols, t2$cols) t3 #> cols( #> column_one = col_integer(), #> column_two = col_number(), #> column_three = col_character() #> )"},{"path":"https://readr.tidyverse.org/dev/reference/count_fields.html","id":null,"dir":"Reference","previous_headings":"","what":"Count the number of fields in each line of a file — count_fields","title":"Count the number of fields in each line of a file — count_fields","text":"useful diagnosing problems functions fail parse correctly.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/count_fields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Count the number of fields in each line of a file — count_fields","text":"","code":"count_fields(file, tokenizer, skip = 0, n_max = -1L)"},{"path":"https://readr.tidyverse.org/dev/reference/count_fields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Count the number of fields in each line of a file — count_fields","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. tokenizer tokenizer specifies break file fields, e.g., tokenizer_csv(), tokenizer_fwf() skip Number lines skip reading data. n_max Optionally, maximum number rows count fields .","code":""},{"path":"https://readr.tidyverse.org/dev/reference/count_fields.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Count the number of fields in each line of a file — count_fields","text":"","code":"count_fields(readr_example(\"mtcars.csv\"), tokenizer_csv()) #> [1] 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 #> [24] 11 11 11 11 11 11 11 11 11 11"},{"path":"https://readr.tidyverse.org/dev/reference/datasource.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a source object. — datasource","title":"Create a source object. — datasource","text":"Create source object.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/datasource.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a source object. — datasource","text":"","code":"datasource( file, skip = 0, skip_empty_rows = FALSE, comment = \"\", skip_quote = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/datasource.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a source object. — datasource","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. skip Number lines skip reading data.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/datasource.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a source object. — datasource","text":"","code":"# Literal csv datasource(\"a,b,c\\n1,2,3\") #> [[1]] #> [1] \"a,b,c\\n1,2,3\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> attr(,\"class\") #> [1] \"source_string\" \"source\" datasource(charToRaw(\"a,b,c\\n1,2,3\")) #> [[1]] #> [1] 61 2c 62 2c 63 0a 31 2c 32 2c 33 #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> attr(,\"class\") #> [1] \"source_raw\" \"source\" # Strings datasource(readr_example(\"mtcars.csv\")) #> [[1]] #> [1] \"/home/runner/work/_temp/Library/readr/extdata/mtcars.csv\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> attr(,\"class\") #> [1] \"source_file\" \"source\" datasource(readr_example(\"mtcars.csv.bz2\")) #> [[1]] #> [1] \"/tmp/RtmpASSHEF/file18137126f20\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> $env #> #> #> attr(,\"class\") #> [1] \"source_file\" \"source\" datasource(readr_example(\"mtcars.csv.zip\")) #> [[1]] #> [1] \"/tmp/RtmpASSHEF/file18135eb33dd6\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> $env #> #> #> attr(,\"class\") #> [1] \"source_file\" \"source\" if (FALSE) { datasource(\"https://github.com/tidyverse/readr/raw/main/inst/extdata/mtcars.csv\") } # Connection con <- rawConnection(charToRaw(\"abc\\n123\")) datasource(con) #> [[1]] #> [1] \"/tmp/RtmpASSHEF/file18131eaee8fc\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> $env #> #> #> attr(,\"class\") #> [1] \"source_file\" \"source\" close(con)"},{"path":"https://readr.tidyverse.org/dev/reference/date_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Create or retrieve date names — date_names","title":"Create or retrieve date names — date_names","text":"parsing dates, often need know weekdays week months represented text. pair functions allows either create , retrieve standard list. standard list derived ICU (http://site.icu-project.org) via stringi package.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/date_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create or retrieve date names — date_names","text":"","code":"date_names(mon, mon_ab = mon, day, day_ab = day, am_pm = c(\"AM\", \"PM\")) date_names_lang(language) date_names_langs()"},{"path":"https://readr.tidyverse.org/dev/reference/date_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create or retrieve date names — date_names","text":"mon, mon_ab Full abbreviated month names. day, day_ab Full abbreviated week day names. Starts Sunday. am_pm Names used PM. language BCP 47 locale, made language region, e.g. \"en\" American English. See date_names_langs() complete list available locales.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/date_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create or retrieve date names — date_names","text":"","code":"date_names_lang(\"en\") #> #> Days: Sunday (Sun), Monday (Mon), Tuesday (Tue), Wednesday (Wed), #> Thursday (Thu), Friday (Fri), Saturday (Sat) #> Months: January (Jan), February (Feb), March (Mar), April (Apr), May #> (May), June (Jun), July (Jul), August (Aug), September #> (Sep), October (Oct), November (Nov), December (Dec) #> AM/PM: AM/PM date_names_lang(\"ko\") #> #> Days: 일요일 (일), 월요일 (월), 화요일 (화), 수요일 (수), 목요일 (목), #> 금요일 (금), 토요일 (토) #> Months: 1월, 2월, 3월, 4월, 5월, 6월, 7월, 8월, 9월, 10월, 11월, 12월 #> AM/PM: 오전/오후 date_names_lang(\"fr\") #> #> Days: dimanche (dim.), lundi (lun.), mardi (mar.), mercredi (mer.), #> jeudi (jeu.), vendredi (ven.), samedi (sam.) #> Months: janvier (janv.), février (févr.), mars (mars), avril (avr.), mai #> (mai), juin (juin), juillet (juil.), août (août), #> septembre (sept.), octobre (oct.), novembre (nov.), #> décembre (déc.) #> AM/PM: AM/PM"},{"path":"https://readr.tidyverse.org/dev/reference/edition_get.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve the currently active edition — edition_get","title":"Retrieve the currently active edition — edition_get","text":"Retrieve currently active edition","code":""},{"path":"https://readr.tidyverse.org/dev/reference/edition_get.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve the currently active edition — edition_get","text":"","code":"edition_get()"},{"path":"https://readr.tidyverse.org/dev/reference/edition_get.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve the currently active edition — edition_get","text":"integer corresponding currently active edition.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/edition_get.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieve the currently active edition — edition_get","text":"","code":"edition_get() #> [1] 2"},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":null,"dir":"Reference","previous_headings":"","what":"Guess encoding of file — guess_encoding","title":"Guess encoding of file — guess_encoding","text":"Uses stringi::stri_enc_detect(): see documentation caveats.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Guess encoding of file — guess_encoding","text":"","code":"guess_encoding(file, n_max = 10000, threshold = 0.2)"},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Guess encoding of file — guess_encoding","text":"file character string specifying input specified datasource(), raw vector, list raw vectors. n_max Number lines read. n_max -1, lines file read. threshold report guesses threshold certainty.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Guess encoding of file — guess_encoding","text":"tibble","code":""},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Guess encoding of file — guess_encoding","text":"","code":"guess_encoding(readr_example(\"mtcars.csv\")) #> # A tibble: 1 × 2 #> encoding confidence #> #> 1 ASCII 1 guess_encoding(read_lines_raw(readr_example(\"mtcars.csv\"))) #> # A tibble: 1 × 2 #> encoding confidence #> #> 1 ASCII 1 guess_encoding(read_file_raw(readr_example(\"mtcars.csv\"))) #> # A tibble: 1 × 2 #> encoding confidence #> #> 1 ASCII 1 guess_encoding(\"a\\n\\u00b5\\u00b5\") #> # A tibble: 1 × 2 #> encoding confidence #> #> 1 UTF-8 0.8"},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a data frame to a delimited string — format_delim","title":"Convert a data frame to a delimited string — format_delim","text":"functions equivalent write_csv() etc., instead writing disk, return string.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a data frame to a delimited string — format_delim","text":"","code":"format_delim( x, delim, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", quote_escape = deprecated() ) format_csv( x, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", quote_escape = deprecated() ) format_csv2( x, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", quote_escape = deprecated() ) format_tsv( x, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", quote_escape = deprecated() )"},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a data frame to a delimited string — format_delim","text":"x data frame. delim Delimiter used separate values. Defaults \" \" write_delim(), \",\" write_excel_csv() \";\" write_excel_csv2(). Must single character. na String used missing values. Defaults NA. Missing values never quoted; strings value na always quoted. append FALSE, overwrite existing file. TRUE, append existing file. cases, file exist new file created. col_names FALSE, column names included top file. TRUE, column names included. specified, col_names take opposite value given append. quote handle fields contain characters need quoted. needed - Values quoted needed: contain delimiter, quote, newline. - Quote fields. none - Never quote fields. escape type escape use quotes data. double - quotes escaped doubling . backslash - quotes escaped preceding backslash. none - quotes escaped. eol end line character use. commonly either \"\\n\" Unix style newlines, \"\\r\\n\" Windows style newlines. quote_escape Use escape argument instead.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a data frame to a delimited string — format_delim","text":"string.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"output","dir":"Reference","previous_headings":"","what":"Output","title":"Convert a data frame to a delimited string — format_delim","text":"Factors coerced character. Doubles formatted decimal string using grisu3 algorithm. POSIXct values formatted ISO8601 UTC timezone Note: POSIXct objects local non-UTC timezones converted UTC time writing. columns encoded UTF-8. write_excel_csv() write_excel_csv2() also include UTF-8 Byte order mark indicates Excel csv UTF-8 encoded. write_excel_csv2() write_csv2 created allow users different locale settings save .csv files using default settings (e.g. ; column separator , decimal separator). common European countries. Values quoted contain comma, quote newline. write_*() functions automatically compress outputs appropriate extension given. Three extensions currently supported: .gz gzip compression, .bz2 bzip2 compression .xz lzma compression. See examples information.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Convert a data frame to a delimited string — format_delim","text":"Florian Loitsch, Printing Floating-Point Numbers Quickly Accurately Integers, PLDI '10, http://www.cs.tufts.edu/~nr/cs257/archive/florian-loitsch/printf.pdf","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a data frame to a delimited string — format_delim","text":"","code":"# format_()* functions are useful for testing and reprexes cat(format_csv(mtcars)) #> mpg,cyl,disp,hp,drat,wt,qsec,vs,am,gear,carb #> 21,6,160,110,3.9,2.62,16.46,0,1,4,4 #> 21,6,160,110,3.9,2.875,17.02,0,1,4,4 #> 22.8,4,108,93,3.85,2.32,18.61,1,1,4,1 #> 21.4,6,258,110,3.08,3.215,19.44,1,0,3,1 #> 18.7,8,360,175,3.15,3.44,17.02,0,0,3,2 #> 18.1,6,225,105,2.76,3.46,20.22,1,0,3,1 #> 14.3,8,360,245,3.21,3.57,15.84,0,0,3,4 #> 24.4,4,146.7,62,3.69,3.19,20,1,0,4,2 #> 22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2 #> 19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4 #> 17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4 #> 16.4,8,275.8,180,3.07,4.07,17.4,0,0,3,3 #> 17.3,8,275.8,180,3.07,3.73,17.6,0,0,3,3 #> 15.2,8,275.8,180,3.07,3.78,18,0,0,3,3 #> 10.4,8,472,205,2.93,5.25,17.98,0,0,3,4 #> 10.4,8,460,215,3,5.424,17.82,0,0,3,4 #> 14.7,8,440,230,3.23,5.345,17.42,0,0,3,4 #> 32.4,4,78.7,66,4.08,2.2,19.47,1,1,4,1 #> 30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2 #> 33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1 #> 21.5,4,120.1,97,3.7,2.465,20.01,1,0,3,1 #> 15.5,8,318,150,2.76,3.52,16.87,0,0,3,2 #> 15.2,8,304,150,3.15,3.435,17.3,0,0,3,2 #> 13.3,8,350,245,3.73,3.84,15.41,0,0,3,4 #> 19.2,8,400,175,3.08,3.845,17.05,0,0,3,2 #> 27.3,4,79,66,4.08,1.935,18.9,1,1,4,1 #> 26,4,120.3,91,4.43,2.14,16.7,0,1,5,2 #> 30.4,4,95.1,113,3.77,1.513,16.9,1,1,5,2 #> 15.8,8,351,264,4.22,3.17,14.5,0,1,5,4 #> 19.7,6,145,175,3.62,2.77,15.5,0,1,5,6 #> 15,8,301,335,3.54,3.57,14.6,0,1,5,8 #> 21.4,4,121,109,4.11,2.78,18.6,1,1,4,2 cat(format_tsv(mtcars)) #> mpg\tcyl\tdisp\thp\tdrat\twt\tqsec\tvs\tam\tgear\tcarb #> 21\t6\t160\t110\t3.9\t2.62\t16.46\t0\t1\t4\t4 #> 21\t6\t160\t110\t3.9\t2.875\t17.02\t0\t1\t4\t4 #> 22.8\t4\t108\t93\t3.85\t2.32\t18.61\t1\t1\t4\t1 #> 21.4\t6\t258\t110\t3.08\t3.215\t19.44\t1\t0\t3\t1 #> 18.7\t8\t360\t175\t3.15\t3.44\t17.02\t0\t0\t3\t2 #> 18.1\t6\t225\t105\t2.76\t3.46\t20.22\t1\t0\t3\t1 #> 14.3\t8\t360\t245\t3.21\t3.57\t15.84\t0\t0\t3\t4 #> 24.4\t4\t146.7\t62\t3.69\t3.19\t20\t1\t0\t4\t2 #> 22.8\t4\t140.8\t95\t3.92\t3.15\t22.9\t1\t0\t4\t2 #> 19.2\t6\t167.6\t123\t3.92\t3.44\t18.3\t1\t0\t4\t4 #> 17.8\t6\t167.6\t123\t3.92\t3.44\t18.9\t1\t0\t4\t4 #> 16.4\t8\t275.8\t180\t3.07\t4.07\t17.4\t0\t0\t3\t3 #> 17.3\t8\t275.8\t180\t3.07\t3.73\t17.6\t0\t0\t3\t3 #> 15.2\t8\t275.8\t180\t3.07\t3.78\t18\t0\t0\t3\t3 #> 10.4\t8\t472\t205\t2.93\t5.25\t17.98\t0\t0\t3\t4 #> 10.4\t8\t460\t215\t3\t5.424\t17.82\t0\t0\t3\t4 #> 14.7\t8\t440\t230\t3.23\t5.345\t17.42\t0\t0\t3\t4 #> 32.4\t4\t78.7\t66\t4.08\t2.2\t19.47\t1\t1\t4\t1 #> 30.4\t4\t75.7\t52\t4.93\t1.615\t18.52\t1\t1\t4\t2 #> 33.9\t4\t71.1\t65\t4.22\t1.835\t19.9\t1\t1\t4\t1 #> 21.5\t4\t120.1\t97\t3.7\t2.465\t20.01\t1\t0\t3\t1 #> 15.5\t8\t318\t150\t2.76\t3.52\t16.87\t0\t0\t3\t2 #> 15.2\t8\t304\t150\t3.15\t3.435\t17.3\t0\t0\t3\t2 #> 13.3\t8\t350\t245\t3.73\t3.84\t15.41\t0\t0\t3\t4 #> 19.2\t8\t400\t175\t3.08\t3.845\t17.05\t0\t0\t3\t2 #> 27.3\t4\t79\t66\t4.08\t1.935\t18.9\t1\t1\t4\t1 #> 26\t4\t120.3\t91\t4.43\t2.14\t16.7\t0\t1\t5\t2 #> 30.4\t4\t95.1\t113\t3.77\t1.513\t16.9\t1\t1\t5\t2 #> 15.8\t8\t351\t264\t4.22\t3.17\t14.5\t0\t1\t5\t4 #> 19.7\t6\t145\t175\t3.62\t2.77\t15.5\t0\t1\t5\t6 #> 15\t8\t301\t335\t3.54\t3.57\t14.6\t0\t1\t5\t8 #> 21.4\t4\t121\t109\t4.11\t2.78\t18.6\t1\t1\t4\t2 cat(format_delim(mtcars, \";\")) #> mpg;cyl;disp;hp;drat;wt;qsec;vs;am;gear;carb #> 21;6;160;110;3.9;2.62;16.46;0;1;4;4 #> 21;6;160;110;3.9;2.875;17.02;0;1;4;4 #> 22.8;4;108;93;3.85;2.32;18.61;1;1;4;1 #> 21.4;6;258;110;3.08;3.215;19.44;1;0;3;1 #> 18.7;8;360;175;3.15;3.44;17.02;0;0;3;2 #> 18.1;6;225;105;2.76;3.46;20.22;1;0;3;1 #> 14.3;8;360;245;3.21;3.57;15.84;0;0;3;4 #> 24.4;4;146.7;62;3.69;3.19;20;1;0;4;2 #> 22.8;4;140.8;95;3.92;3.15;22.9;1;0;4;2 #> 19.2;6;167.6;123;3.92;3.44;18.3;1;0;4;4 #> 17.8;6;167.6;123;3.92;3.44;18.9;1;0;4;4 #> 16.4;8;275.8;180;3.07;4.07;17.4;0;0;3;3 #> 17.3;8;275.8;180;3.07;3.73;17.6;0;0;3;3 #> 15.2;8;275.8;180;3.07;3.78;18;0;0;3;3 #> 10.4;8;472;205;2.93;5.25;17.98;0;0;3;4 #> 10.4;8;460;215;3;5.424;17.82;0;0;3;4 #> 14.7;8;440;230;3.23;5.345;17.42;0;0;3;4 #> 32.4;4;78.7;66;4.08;2.2;19.47;1;1;4;1 #> 30.4;4;75.7;52;4.93;1.615;18.52;1;1;4;2 #> 33.9;4;71.1;65;4.22;1.835;19.9;1;1;4;1 #> 21.5;4;120.1;97;3.7;2.465;20.01;1;0;3;1 #> 15.5;8;318;150;2.76;3.52;16.87;0;0;3;2 #> 15.2;8;304;150;3.15;3.435;17.3;0;0;3;2 #> 13.3;8;350;245;3.73;3.84;15.41;0;0;3;4 #> 19.2;8;400;175;3.08;3.845;17.05;0;0;3;2 #> 27.3;4;79;66;4.08;1.935;18.9;1;1;4;1 #> 26;4;120.3;91;4.43;2.14;16.7;0;1;5;2 #> 30.4;4;95.1;113;3.77;1.513;16.9;1;1;5;2 #> 15.8;8;351;264;4.22;3.17;14.5;0;1;5;4 #> 19.7;6;145;175;3.62;2.77;15.5;0;1;5;6 #> 15;8;301;335;3.54;3.57;14.6;0;1;5;8 #> 21.4;4;121;109;4.11;2.78;18.6;1;1;4;2 # Specifying missing values df <- data.frame(x = c(1, NA, 3)) format_csv(df, na = \"missing\") #> [1] \"x\\n1\\nmissing\\n3\\n\" # Quotes are automatically added as needed df <- data.frame(x = c(\"a \", '\"', \",\", \"\\n\")) cat(format_csv(df)) #> x #> a #> \"\"\"\" #> \",\" #> \" #> \""},{"path":"https://readr.tidyverse.org/dev/reference/locale.html","id":null,"dir":"Reference","previous_headings":"","what":"Create locales — locale","title":"Create locales — locale","text":"locale object tries capture defaults can vary countries. set locale , details automatically passed columns parsers. defaults chosen match R (.e. US English) closely possible. See vignette(\"locales\") details.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/locale.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create locales — locale","text":"","code":"locale( date_names = \"en\", date_format = \"%AD\", time_format = \"%AT\", decimal_mark = \".\", grouping_mark = \",\", tz = \"UTC\", encoding = \"UTF-8\", asciify = FALSE ) default_locale()"},{"path":"https://readr.tidyverse.org/dev/reference/locale.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create locales — locale","text":"date_names Character representations day month names. Either language code string (passed date_names_lang()) object created date_names(). date_format, time_format Default date time formats. decimal_mark, grouping_mark Symbols used indicate decimal place, chunk larger numbers. Decimal mark can , .. tz Default tz. used input (time zone present individual strings), output (control default display). default use \"UTC\", time zone use daylight savings time (DST) hence typically useful data. absence time zones makes approximately 50x faster generate UTC times time zone. Use \"\" use system default time zone, beware reproducible across systems. complete list possible time zones, see OlsonNames(). Americans, note \"EST\" Canadian time zone DST. Eastern Standard Time. better use \"US/Eastern\", \"US/Central\" etc. encoding Default encoding. affects file read - readr always converts output UTF-8. asciify diacritics stripped date names converted ASCII? useful dealing ASCII data correct spellings lost. Requires stringi package.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/locale.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create locales — locale","text":"","code":"locale() #> #> Numbers: 123,456.78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: Sunday (Sun), Monday (Mon), Tuesday (Tue), Wednesday (Wed), #> Thursday (Thu), Friday (Fri), Saturday (Sat) #> Months: January (Jan), February (Feb), March (Mar), April (Apr), May #> (May), June (Jun), July (Jul), August (Aug), September #> (Sep), October (Oct), November (Nov), December (Dec) #> AM/PM: AM/PM locale(\"fr\") #> #> Numbers: 123,456.78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: dimanche (dim.), lundi (lun.), mardi (mar.), mercredi (mer.), #> jeudi (jeu.), vendredi (ven.), samedi (sam.) #> Months: janvier (janv.), février (févr.), mars (mars), avril (avr.), mai #> (mai), juin (juin), juillet (juil.), août (août), #> septembre (sept.), octobre (oct.), novembre (nov.), #> décembre (déc.) #> AM/PM: AM/PM # South American locale locale(\"es\", decimal_mark = \",\") #> #> Numbers: 123.456,78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: domingo (dom.), lunes (lun.), martes (mar.), miércoles (mié.), #> jueves (jue.), viernes (vie.), sábado (sáb.) #> Months: enero (ene.), febrero (feb.), marzo (mar.), abril (abr.), mayo #> (may.), junio (jun.), julio (jul.), agosto (ago.), #> septiembre (sept.), octubre (oct.), noviembre (nov.), #> diciembre (dic.) #> AM/PM: a. m./p. m."},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"function superseded readr moved meltr package.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"","code":"melt_delim( file, delim, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE ) melt_csv( file, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE ) melt_csv2( file, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE ) melt_tsv( file, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. delim Single character used separate fields within record. quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. n_max Maximum number lines read. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"tibble() four columns: row, row token comes original file col, column token comes original file data_type, data type token, e.g. \"integer\", \"character\", \"date\", guessed similar way guess_parser() function. value, token character string, unchanged representation original file. parsing problems, warning tells many, can retrieve details problems().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"certain non-rectangular data formats, can useful parse data melted format row represents single token. melt_csv() melt_tsv() special cases general melt_delim(). useful reading common types flat file data, comma separated values tab separated values, respectively. melt_csv2() uses ; field separator , decimal point. common European countries.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"","code":"# Input sources ------------------------------------------------------------- # Read from a path melt_csv(readr_example(\"mtcars.csv\")) #> Warning: `melt_csv()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_csv()` instead #> # A tibble: 363 × 4 #> row col data_type value #> #> 1 1 1 character mpg #> 2 1 2 character cyl #> 3 1 3 character disp #> 4 1 4 character hp #> 5 1 5 character drat #> 6 1 6 character wt #> 7 1 7 character qsec #> 8 1 8 character vs #> 9 1 9 character am #> 10 1 10 character gear #> # ℹ 353 more rows melt_csv(readr_example(\"mtcars.csv.zip\")) #> # A tibble: 363 × 4 #> row col data_type value #> #> 1 1 1 character mpg #> 2 1 2 character cyl #> 3 1 3 character disp #> 4 1 4 character hp #> 5 1 5 character drat #> 6 1 6 character wt #> 7 1 7 character qsec #> 8 1 8 character vs #> 9 1 9 character am #> 10 1 10 character gear #> # ℹ 353 more rows melt_csv(readr_example(\"mtcars.csv.bz2\")) #> # A tibble: 363 × 4 #> row col data_type value #> #> 1 1 1 character mpg #> 2 1 2 character cyl #> 3 1 3 character disp #> 4 1 4 character hp #> 5 1 5 character drat #> 6 1 6 character wt #> 7 1 7 character qsec #> 8 1 8 character vs #> 9 1 9 character am #> 10 1 10 character gear #> # ℹ 353 more rows if (FALSE) { melt_csv(\"https://github.com/tidyverse/readr/raw/main/inst/extdata/mtcars.csv\") } # Or directly from a string (must contain a newline) melt_csv(\"x,y\\n1,2\\n3,4\") #> # A tibble: 6 × 4 #> row col data_type value #> #> 1 1 1 character x #> 2 1 2 character y #> 3 2 1 integer 1 #> 4 2 2 integer 2 #> 5 3 1 integer 3 #> 6 3 2 integer 4 # To import empty cells as 'empty' rather than `NA` melt_csv(\"x,y\\n,NA,\\\"\\\",''\", na = \"NA\") #> # A tibble: 6 × 4 #> row col data_type value #> #> 1 1 1 character \"x\" #> 2 1 2 character \"y\" #> 3 2 1 empty \"\" #> 4 2 2 missing NA #> 5 2 3 empty \"\" #> 6 2 4 character \"''\" # File types ---------------------------------------------------------------- melt_csv(\"a,b\\n1.0,2.0\") #> # A tibble: 4 × 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 2 1 double 1.0 #> 4 2 2 double 2.0 melt_csv2(\"a;b\\n1,0;2,0\") #> Warning: `melt_csv2()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_csv2()` instead #> ℹ Using \"','\" as decimal and \"'.'\" as grouping mark. Use `read_delim()` for more control. #> # A tibble: 4 × 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 2 1 double 1,0 #> 4 2 2 double 2,0 melt_tsv(\"a\\tb\\n1.0\\t2.0\") #> Warning: `melt_tsv()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_tsv()` instead #> # A tibble: 4 × 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 2 1 double 1.0 #> 4 2 2 double 2.0 melt_delim(\"a|b\\n1.0|2.0\", delim = \"|\") #> Warning: `melt_delim()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_delim()` instead #> # A tibble: 4 × 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 2 1 double 1.0 #> 4 2 2 double 2.0"},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":null,"dir":"Reference","previous_headings":"","what":"Melt a delimited file by chunks — melt_delim_chunked","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"certain non-rectangular data formats, can useful parse data melted format row represents single token.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"","code":"melt_delim_chunked( file, callback, chunk_size = 10000, delim, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, progress = show_progress(), skip_empty_rows = FALSE ) melt_csv_chunked( file, callback, chunk_size = 10000, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, progress = show_progress(), skip_empty_rows = FALSE ) melt_csv2_chunked( file, callback, chunk_size = 10000, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, progress = show_progress(), skip_empty_rows = FALSE ) melt_tsv_chunked( file, callback, chunk_size = 10000, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, progress = show_progress(), skip_empty_rows = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. callback callback function call chunk chunk_size number rows include chunk delim Single character used separate fields within record. quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"melt_delim_chunked() specialisations melt_csv_chunked(), melt_csv2_chunked() melt_tsv_chunked() read files chunk rows time, executing given function one chunk reading next.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"","code":"# Cars with 3 gears f <- function(x, pos) subset(x, data_type == \"integer\") melt_csv_chunked(readr_example(\"mtcars.csv\"), DataFrameCallback$new(f), chunk_size = 5) #> # A tibble: 218 × 4 #> row col data_type value #> #> 1 2 1 integer 21 #> 2 2 2 integer 6 #> 3 2 3 integer 160 #> 4 2 4 integer 110 #> 5 2 8 integer 0 #> 6 2 9 integer 1 #> 7 2 10 integer 4 #> 8 2 11 integer 4 #> 9 3 1 integer 21 #> 10 3 2 integer 6 #> # ℹ 208 more rows"},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":null,"dir":"Reference","previous_headings":"","what":"Return melted data for each token in a fixed width file — melt_fwf","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"function superseded readr moved meltr package.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"","code":"melt_fwf( file, col_positions, locale = default_locale(), na = c(\"\", \"NA\"), comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. col_positions Column positions, created fwf_empty(), fwf_widths() fwf_positions(). read selected fields, use fwf_positions(). width last column variable (ragged fwf file), supply last end position NA. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. n_max Maximum number lines read. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"certain non-rectangular data formats, can useful parse data melted format row represents single token. melt_fwf() parses token fixed width file single row, still requires field every row source file.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"","code":"fwf_sample <- readr_example(\"fwf-sample.txt\") cat(read_lines(fwf_sample)) #> John Smith WA 418-Y11-4111 Mary Hartford CA 319-Z19-4341 Evan Nolan IL 219-532-c301 # You can specify column positions in several ways: # 1. Guess based on position of empty columns melt_fwf(fwf_sample, fwf_empty(fwf_sample, col_names = c(\"first\", \"last\", \"state\", \"ssn\"))) #> Warning: `melt_fwf()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_fwf()` instead #> # A tibble: 12 × 4 #> row col data_type value #> #> 1 1 1 character John #> 2 1 2 character Smith #> 3 1 3 character WA #> 4 1 4 character 418-Y11-4111 #> 5 2 1 character Mary #> 6 2 2 character Hartford #> 7 2 3 character CA #> 8 2 4 character 319-Z19-4341 #> 9 3 1 character Evan #> 10 3 2 character Nolan #> 11 3 3 character IL #> 12 3 4 character 219-532-c301 # 2. A vector of field widths melt_fwf(fwf_sample, fwf_widths(c(20, 10, 12), c(\"name\", \"state\", \"ssn\"))) #> # A tibble: 9 × 4 #> row col data_type value #> #> 1 1 1 character John Smith #> 2 1 2 character WA #> 3 1 3 character 418-Y11-4111 #> 4 2 1 character Mary Hartford #> 5 2 2 character CA #> 6 2 3 character 319-Z19-4341 #> 7 3 1 character Evan Nolan #> 8 3 2 character IL #> 9 3 3 character 219-532-c301 # 3. Paired vectors of start and end positions melt_fwf(fwf_sample, fwf_positions(c(1, 30), c(10, 42), c(\"name\", \"ssn\"))) #> # A tibble: 6 × 4 #> row col data_type value #> #> 1 1 1 character John Smith #> 2 1 2 character 418-Y11-4111 #> 3 2 1 character Mary Hartf #> 4 2 2 character 319-Z19-4341 #> 5 3 1 character Evan Nolan #> 6 3 2 character 219-532-c301 # 4. Named arguments with start and end positions melt_fwf(fwf_sample, fwf_cols(name = c(1, 10), ssn = c(30, 42))) #> # A tibble: 6 × 4 #> row col data_type value #> #> 1 1 1 character John Smith #> 2 1 2 character 418-Y11-4111 #> 3 2 1 character Mary Hartf #> 4 2 2 character 319-Z19-4341 #> 5 3 1 character Evan Nolan #> 6 3 2 character 219-532-c301 # 5. Named arguments with column widths melt_fwf(fwf_sample, fwf_cols(name = 20, state = 10, ssn = 12)) #> # A tibble: 9 × 4 #> row col data_type value #> #> 1 1 1 character John Smith #> 2 1 2 character WA #> 3 1 3 character 418-Y11-4111 #> 4 2 1 character Mary Hartford #> 5 2 2 character CA #> 6 2 3 character 319-Z19-4341 #> 7 3 1 character Evan Nolan #> 8 3 2 character IL #> 9 3 3 character 219-532-c301"},{"path":"https://readr.tidyverse.org/dev/reference/melt_table.html","id":null,"dir":"Reference","previous_headings":"","what":"Return melted data for each token in a whitespace-separated file — melt_table","title":"Return melted data for each token in a whitespace-separated file — melt_table","text":"function superseded readr moved meltr package. certain non-rectangular data formats, can useful parse data melted format row represents single token. melt_table() melt_table2() designed read type textual data column separated one () columns space. melt_table2() allows number whitespace characters columns, lines can different lengths. melt_table() strict, line must length, field position every line. first finds empty columns parses like fixed width file.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_table.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return melted data for each token in a whitespace-separated file — melt_table","text":"","code":"melt_table( file, locale = default_locale(), na = \"NA\", skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress(), comment = \"\", skip_empty_rows = FALSE ) melt_table2( file, locale = default_locale(), na = \"NA\", skip = 0, n_max = Inf, progress = show_progress(), comment = \"\", skip_empty_rows = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/melt_table.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return melted data for each token in a whitespace-separated file — melt_table","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. skip Number lines skip reading data. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. comment string used identify comments. text comment characters silently ignored. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/melt_table.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return melted data for each token in a whitespace-separated file — melt_table","text":"","code":"fwf <- readr_example(\"fwf-sample.txt\") writeLines(read_lines(fwf)) #> John Smith WA 418-Y11-4111 #> Mary Hartford CA 319-Z19-4341 #> Evan Nolan IL 219-532-c301 melt_table(fwf) #> Warning: `melt_table()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_table()` instead #> # A tibble: 12 × 4 #> row col data_type value #> #> 1 1 1 character John #> 2 1 2 character Smith #> 3 1 3 character WA #> 4 1 4 character 418-Y11-4111 #> 5 2 1 character Mary #> 6 2 2 character Hartford #> 7 2 3 character CA #> 8 2 4 character 319-Z19-4341 #> 9 3 1 character Evan #> 10 3 2 character Nolan #> 11 3 3 character IL #> 12 3 4 character 219-532-c301 ws <- readr_example(\"whitespace-sample.txt\") writeLines(read_lines(ws)) #> first last state phone #> John Smith WA 418-Y11-4111 #> Mary Hartford CA 319-Z19-4341 #> Evan Nolan IL 219-532-c301 melt_table2(ws) #> Warning: `melt_table2()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_table2()` instead #> # A tibble: 16 × 4 #> row col data_type value #> #> 1 1 1 character first #> 2 1 2 character last #> 3 1 3 character state #> 4 1 4 character phone #> 5 2 1 character John #> 6 2 2 character Smith #> 7 2 3 character WA #> 8 2 4 character 418-Y11-4111 #> 9 3 1 character Mary #> 10 3 2 character Hartford #> 11 3 3 character CA #> 12 3 4 character 319-Z19-4341 #> 13 4 1 character Evan #> 14 4 2 character Nolan #> 15 4 3 character IL #> 16 4 4 character 219-532-c301"},{"path":"https://readr.tidyverse.org/dev/reference/output_column.html","id":null,"dir":"Reference","previous_headings":"","what":"Preprocess column for output — output_column","title":"Preprocess column for output — output_column","text":"generic function applied column saved disk. provides hook S3 classes need special handling.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/output_column.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Preprocess column for output — output_column","text":"","code":"output_column(x, name)"},{"path":"https://readr.tidyverse.org/dev/reference/output_column.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Preprocess column for output — output_column","text":"x vector","code":""},{"path":"https://readr.tidyverse.org/dev/reference/output_column.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Preprocess column for output — output_column","text":"","code":"# Most columns are not altered, but POSIXct are converted to ISO8601. x <- parse_datetime(\"2016-01-01\") str(output_column(x)) #> chr \"2016-01-01T00:00:00Z\""},{"path":"https://readr.tidyverse.org/dev/reference/parse_atomic.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse logicals, integers, and reals — parse_atomic","title":"Parse logicals, integers, and reals — parse_atomic","text":"Use parse_*() character vector want parse. Use col_*() conjunction read_*() function parse values read .","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_atomic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse logicals, integers, and reals — parse_atomic","text":"","code":"parse_logical(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) parse_integer(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) parse_double(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) parse_character(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) col_logical() col_integer() col_double() col_character()"},{"path":"https://readr.tidyverse.org/dev/reference/parse_atomic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse logicals, integers, and reals — parse_atomic","text":"x Character vector values parse. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_atomic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse logicals, integers, and reals — parse_atomic","text":"","code":"parse_integer(c(\"1\", \"2\", \"3\")) #> [1] 1 2 3 parse_double(c(\"1\", \"2\", \"3.123\")) #> [1] 1.000 2.000 3.123 parse_number(\"$1,123,456.00\") #> [1] 1123456 # Use locale to override default decimal and grouping marks es_MX <- locale(\"es\", decimal_mark = \",\") parse_number(\"$1.123.456,00\", locale = es_MX) #> [1] 1123456 # Invalid values are replaced with missing values with a warning. x <- c(\"1\", \"2\", \"3\", \"-\") parse_double(x) #> Warning: 1 parsing failure. #> row col expected actual #> 4 -- a double - #> [1] 1 2 3 NA #> attr(,\"problems\") #> # A tibble: 1 × 4 #> row col expected actual #> #> 1 4 NA a double - # Or flag values as missing parse_double(x, na = \"-\") #> [1] 1 2 3 NA"},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse date/times — parse_datetime","title":"Parse date/times — parse_datetime","text":"Parse date/times","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse date/times — parse_datetime","text":"","code":"parse_datetime( x, format = \"\", na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE ) parse_date( x, format = \"\", na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE ) parse_time( x, format = \"\", na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE ) col_datetime(format = \"\") col_date(format = \"\") col_time(format = \"\")"},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse date/times — parse_datetime","text":"x character vector dates parse. format format specification, described . set \"\", date times parsed ISO8601, dates times used date time formats specified locale(). Unlike strptime(), format specification must match complete string. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Parse date/times — parse_datetime","text":"POSIXct() vector tzone attribute set tz. Elements parsed (generate valid dates) set NA, warning message inform total number failures.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"format-specification","dir":"Reference","previous_headings":"","what":"Format specification","title":"Parse date/times — parse_datetime","text":"readr uses format specification similar strptime(). three types element: Date components specified \"%\" followed letter. example \"%Y\" matches 4 digit year, \"%m\", matches 2 digit month \"%d\" matches 2 digit day. Month day default 1, (.e. Jan 1st) present, example year given. Whitespace sequence zero whitespace characters. character matched exactly. parse_datetime() recognises following format specifications: Year: \"%Y\" (4 digits). \"%y\" (2 digits); 00-69 -> 2000-2069, 70-99 -> 1970-1999. Month: \"%m\" (2 digits), \"%b\" (abbreviated name current locale), \"%B\" (full name current locale). Day: \"%d\" (2 digits), \"%e\" (optional leading space), \"%\" (abbreviated name current locale). Hour: \"%H\" \"%\" \"%h\", use (H) /PM, use h (H) times represent durations longer one day. Minutes: \"%M\" Seconds: \"%S\" (integer seconds), \"%OS\" (partial seconds) Time zone: \"%Z\" (name, e.g. \"America/Chicago\"), \"%z\" (offset UTC, e.g. \"+0800\") /PM indicator: \"%p\". Non-digits: \"%.\" skips one non-digit character, \"%+\" skips one non-digit characters, \"%*\" skips number non-digits characters. Automatic parsers: \"%AD\" parses flexible YMD parser, \"%\" parses flexible HMS parser. Time since Unix epoch: \"%s\" decimal seconds since Unix epoch. Shortcuts: \"%D\" = \"%m/%d/%y\", \"%F\" = \"%Y-%m-%d\", \"%R\" = \"%H:%M\", \"%T\" = \"%H:%M:%S\", \"%x\" = \"%y/%m/%d\".","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"iso-support","dir":"Reference","previous_headings":"","what":"ISO8601 support","title":"Parse date/times — parse_datetime","text":"Currently, readr support ISO8601. Missing features: Week & weekday specifications, e.g. \"2013-W05\", \"2013-W05-10\". Ordinal dates, e.g. \"2013-095\". Using commas instead period decimal separator. parser also little laxer ISO8601: Dates times can separated space, just T. Mostly correct specifications like \"2009-05-19 14:\" \"200912-01\" work.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse date/times — parse_datetime","text":"","code":"# Format strings -------------------------------------------------------- parse_datetime(\"01/02/2010\", \"%d/%m/%Y\") #> [1] \"2010-02-01 UTC\" parse_datetime(\"01/02/2010\", \"%m/%d/%Y\") #> [1] \"2010-01-02 UTC\" # Handle any separator parse_datetime(\"01/02/2010\", \"%m%.%d%.%Y\") #> [1] \"2010-01-02 UTC\" # Dates look the same, but internally they use the number of days since # 1970-01-01 instead of the number of seconds. This avoids a whole lot # of troubles related to time zones, so use if you can. parse_date(\"01/02/2010\", \"%d/%m/%Y\") #> [1] \"2010-02-01\" parse_date(\"01/02/2010\", \"%m/%d/%Y\") #> [1] \"2010-01-02\" # You can parse timezones from strings (as listed in OlsonNames()) parse_datetime(\"2010/01/01 12:00 US/Central\", \"%Y/%m/%d %H:%M %Z\") #> [1] \"2010-01-01 18:00:00 UTC\" # Or from offsets parse_datetime(\"2010/01/01 12:00 -0600\", \"%Y/%m/%d %H:%M %z\") #> [1] \"2010-01-01 18:00:00 UTC\" # Use the locale parameter to control the default time zone # (but note UTC is considerably faster than other options) parse_datetime(\"2010/01/01 12:00\", \"%Y/%m/%d %H:%M\", locale = locale(tz = \"US/Central\") ) #> [1] \"2010-01-01 12:00:00 CST\" parse_datetime(\"2010/01/01 12:00\", \"%Y/%m/%d %H:%M\", locale = locale(tz = \"US/Eastern\") ) #> [1] \"2010-01-01 12:00:00 EST\" # Unlike strptime, the format specification must match the complete # string (ignoring leading and trailing whitespace). This avoids common # errors: strptime(\"01/02/2010\", \"%d/%m/%y\") #> [1] \"2020-02-01 UTC\" parse_datetime(\"01/02/2010\", \"%d/%m/%y\") #> Warning: 1 parsing failure. #> row col expected actual #> 1 -- date like %d/%m/%y 01/02/2010 #> [1] NA # Failures ------------------------------------------------------------- parse_datetime(\"01/01/2010\", \"%d/%m/%Y\") #> [1] \"2010-01-01 UTC\" parse_datetime(c(\"01/ab/2010\", \"32/01/2010\"), \"%d/%m/%Y\") #> Warning: 2 parsing failures. #> row col expected actual #> 1 -- date like %d/%m/%Y 01/ab/2010 #> 2 -- valid date 32/01/2010 #> [1] NA NA # Locales -------------------------------------------------------------- # By default, readr expects English date/times, but that's easy to change' parse_datetime(\"1 janvier 2015\", \"%d %B %Y\", locale = locale(\"fr\")) #> [1] \"2015-01-01 UTC\" parse_datetime(\"1 enero 2015\", \"%d %B %Y\", locale = locale(\"es\")) #> [1] \"2015-01-01 UTC\" # ISO8601 -------------------------------------------------------------- # With separators parse_datetime(\"1979-10-14\") #> [1] \"1979-10-14 UTC\" parse_datetime(\"1979-10-14T10\") #> [1] \"1979-10-14 10:00:00 UTC\" parse_datetime(\"1979-10-14T10:11\") #> [1] \"1979-10-14 10:11:00 UTC\" parse_datetime(\"1979-10-14T10:11:12\") #> [1] \"1979-10-14 10:11:12 UTC\" parse_datetime(\"1979-10-14T10:11:12.12345\") #> [1] \"1979-10-14 10:11:12 UTC\" # Without separators parse_datetime(\"19791014\") #> [1] \"1979-10-14 UTC\" parse_datetime(\"19791014T101112\") #> [1] \"1979-10-14 10:11:12 UTC\" # Time zones us_central <- locale(tz = \"US/Central\") parse_datetime(\"1979-10-14T1010\", locale = us_central) #> [1] \"1979-10-14 10:10:00 CDT\" parse_datetime(\"1979-10-14T1010-0500\", locale = us_central) #> [1] \"1979-10-14 10:10:00 CDT\" parse_datetime(\"1979-10-14T1010Z\", locale = us_central) #> [1] \"1979-10-14 05:10:00 CDT\" # Your current time zone parse_datetime(\"1979-10-14T1010\", locale = locale(tz = \"\")) #> [1] \"1979-10-14 10:10:00 UTC\""},{"path":"https://readr.tidyverse.org/dev/reference/parse_factor.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse factors — parse_factor","title":"Parse factors — parse_factor","text":"parse_factor() similar factor(), generates warning levels specified elements x found levels.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_factor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse factors — parse_factor","text":"","code":"parse_factor( x, levels = NULL, ordered = FALSE, na = c(\"\", \"NA\"), locale = default_locale(), include_na = TRUE, trim_ws = TRUE ) col_factor(levels = NULL, ordered = FALSE, include_na = FALSE)"},{"path":"https://readr.tidyverse.org/dev/reference/parse_factor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse factors — parse_factor","text":"x Character vector values parse. levels Character vector allowed levels. levels = NULL (default), levels discovered unique values x, order appear x. ordered ordered factor? na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. include_na TRUE x contains least one NA, NA included levels constructed factor. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_factor.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse factors — parse_factor","text":"","code":"# discover the levels from the data parse_factor(c(\"a\", \"b\")) #> [1] a b #> Levels: a b parse_factor(c(\"a\", \"b\", \"-99\")) #> [1] a b -99 #> Levels: a b -99 parse_factor(c(\"a\", \"b\", \"-99\"), na = c(\"\", \"NA\", \"-99\")) #> [1] a b #> Levels: a b parse_factor(c(\"a\", \"b\", \"-99\"), na = c(\"\", \"NA\", \"-99\"), include_na = FALSE) #> [1] a b #> Levels: a b # provide the levels explicitly parse_factor(c(\"a\", \"b\"), levels = letters[1:5]) #> [1] a b #> Levels: a b c d e x <- c(\"cat\", \"dog\", \"caw\") animals <- c(\"cat\", \"dog\", \"cow\") # base::factor() silently converts elements that do not match any levels to # NA factor(x, levels = animals) #> [1] cat dog #> Levels: cat dog cow # parse_factor() generates same factor as base::factor() but throws a warning # and reports problems parse_factor(x, levels = animals) #> Warning: 1 parsing failure. #> row col expected actual #> 3 -- value in level set caw #> [1] cat dog #> attr(,\"problems\") #> # A tibble: 1 × 4 #> row col expected actual #> #> 1 3 NA value in level set caw #> Levels: cat dog cow"},{"path":"https://readr.tidyverse.org/dev/reference/parse_guess.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse using the ","title":"Parse using the ","text":"parse_guess() returns parser vector; guess_parser() returns name parser. functions use number heuristics determine type vector \"best\". Generally try err side safety, straightforward override parsing choice needed.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_guess.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse using the ","text":"","code":"parse_guess( x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE, guess_integer = FALSE ) col_guess() guess_parser( x, locale = default_locale(), guess_integer = FALSE, na = c(\"\", \"NA\") )"},{"path":"https://readr.tidyverse.org/dev/reference/parse_guess.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse using the ","text":"x Character vector values parse. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? guess_integer TRUE, guess integer types whole numbers, FALSE guess numeric type numbers.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_guess.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse using the ","text":"","code":"# Logical vectors parse_guess(c(\"FALSE\", \"TRUE\", \"F\", \"T\")) #> [1] FALSE TRUE FALSE TRUE # Integers and doubles parse_guess(c(\"1\", \"2\", \"3\")) #> [1] 1 2 3 parse_guess(c(\"1.6\", \"2.6\", \"3.4\")) #> [1] 1.6 2.6 3.4 # Numbers containing grouping mark guess_parser(\"1,234,566\") #> [1] \"number\" parse_guess(\"1,234,566\") #> [1] 1234566 # ISO 8601 date times guess_parser(c(\"2010-10-10\")) #> [1] \"date\" parse_guess(c(\"2010-10-10\")) #> [1] \"2010-10-10\""},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse numbers, flexibly — parse_number","title":"Parse numbers, flexibly — parse_number","text":"parses first number finds, dropping non-numeric characters first number characters first number. grouping mark specified locale ignored inside number.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse numbers, flexibly — parse_number","text":"","code":"parse_number(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) col_number()"},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse numbers, flexibly — parse_number","text":"x Character vector values parse. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Parse numbers, flexibly — parse_number","text":"numeric vector (double) parsed numbers.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse numbers, flexibly — parse_number","text":"","code":"## These all return 1000 parse_number(\"$1,000\") ## leading `$` and grouping character `,` ignored #> [1] 1000 parse_number(\"euro1,000\") ## leading non-numeric euro ignored #> [1] 1000 parse_number(\"t1000t1000\") ## only parses first number found #> [1] 1000 parse_number(\"1,234.56\") #> [1] 1234.56 ## explicit locale specifying European grouping and decimal marks parse_number(\"1.234,56\", locale = locale(decimal_mark = \",\", grouping_mark = \".\")) #> [1] 1234.56 ## SI/ISO 31-0 standard spaces for number grouping parse_number(\"1 234.56\", locale = locale(decimal_mark = \".\", grouping_mark = \" \")) #> [1] 1234.56 ## Specifying strings for NAs parse_number(c(\"1\", \"2\", \"3\", \"NA\")) #> [1] 1 2 3 NA parse_number(c(\"1\", \"2\", \"3\", \"NA\", \"Nothing\"), na = c(\"NA\", \"Nothing\")) #> [1] 1 2 3 NA NA"},{"path":"https://readr.tidyverse.org/dev/reference/parse_vector.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse a character vector. — parse_vector","title":"Parse a character vector. — parse_vector","text":"Parse character vector.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_vector.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse a character vector. — parse_vector","text":"","code":"parse_vector( x, collector, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/parse_vector.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse a character vector. — parse_vector","text":"x Character vector elements parse. collector Column specification. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_vector.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse a character vector. — parse_vector","text":"","code":"x <- c(\"1\", \"2\", \"3\", \"NA\") parse_vector(x, col_integer()) #> [1] 1 2 3 NA parse_vector(x, col_double()) #> [1] 1 2 3 NA"},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve parsing problems — problems","title":"Retrieve parsing problems — problems","text":"Readr functions throw error parsing fails unrecoverable way. However, lots potential problems might want know - stored problems attribute output, can easily access function. stop_for_problems() throw error parsing problems: useful automated scripts want throw error soon encounter problem.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve parsing problems — problems","text":"","code":"problems(x = .Last.value) stop_for_problems(x)"},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve parsing problems — problems","text":"x data frame (read_*()) vector (parse_*()).","code":""},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve parsing problems — problems","text":"data frame one row problem four columns: row,col Row column problem expected readr expected find actual actually got","code":""},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieve parsing problems — problems","text":"","code":"x <- parse_integer(c(\"1X\", \"blah\", \"3\")) #> Warning: 2 parsing failures. #> row col expected actual #> 1 -- no trailing characters 1X #> 2 -- no trailing characters blah problems(x) #> # A tibble: 2 × 4 #> row col expected actual #> #> 1 1 NA no trailing characters 1X #> 2 2 NA no trailing characters blah y <- parse_integer(c(\"1\", \"2\", \"3\")) problems(y)"},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":null,"dir":"Reference","previous_headings":"","what":"Read built-in object from package — read_builtin","title":"Read built-in object from package — read_builtin","text":"Consistent wrapper around data() forces promise. also stronger parallel loading data file.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read built-in object from package — read_builtin","text":"","code":"read_builtin(x, package = NULL)"},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read built-in object from package — read_builtin","text":"x Name (character string) data set read. package Name package find data set. default, attached packages searched 'data' subdirectory (present) current working directory.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read built-in object from package — read_builtin","text":"object built-class x.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read built-in object from package — read_builtin","text":"","code":"read_builtin(\"mtcars\", \"datasets\") #> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2"},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"read_csv() read_tsv() special cases general read_delim(). useful reading common types flat file data, comma separated values tab separated values, respectively. read_csv2() uses ; field separator , decimal point. format common European countries.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"","code":"read_delim( file, delim = NULL, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, col_names = TRUE, col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), name_repair = \"unique\", num_threads = readr_threads(), progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) read_csv( file, col_names = TRUE, col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), name_repair = \"unique\", num_threads = readr_threads(), progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) read_csv2( file, col_names = TRUE, col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) read_tsv( file, col_names = TRUE, col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() )"},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. delim Single character used separate fields within record. quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). col_select Columns include results. can use mini-language dplyr::select() refer columns name. Use c() use one selection expression. Although usage less common, col_select also accepts numeric column index. See ?tidyselect::language full details selection language. id name column store file path. useful reading multiple input files data file paths, data collection date. NULL (default) extra column created. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. name_repair Handling column names. default behaviour ensure column names \"unique\". Various repair strategies supported: \"minimal\": name repair checks, beyond basic existence names. \"unique\" (default value): Make sure names unique empty. \"check_unique\": name repair, check unique. \"unique_quiet\": Repair unique strategy, quietly. \"universal\": Make names unique syntactic. \"universal_quiet\": Repair universal strategy, quietly. function: Apply custom name repair (e.g., name_repair = make.names names style base R). purrr-style anonymous function, see rlang::as_function(). argument passed repair vctrs::vec_as_names(). See details terms strategies used enforce . num_threads number processing threads use initial parsing lazy reading data. data contains newlines within fields parser automatically detect fall back using one thread . However know file newlines within quoted fields safest set num_threads = 1 explicitly. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. lazy Read values lazily? default, FALSE, special considerations reading file lazily tripped users. Specifically, things get tricky reading writing back file. , general, lazy reading (lazy = TRUE) many benefits, especially interactive use downstream work involves subset rows columns. Learn should_read_lazy() documentation altrep argument vroom::vroom().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"tibble(). parsing problems, warning alert . can retrieve full details calling problems() dataset.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"","code":"# Input sources ------------------------------------------------------------- # Read from a path read_csv(readr_example(\"mtcars.csv\")) #> Rows: 32 Columns: 11 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 32 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows read_csv(readr_example(\"mtcars.csv.zip\")) #> Rows: 32 Columns: 11 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 32 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows read_csv(readr_example(\"mtcars.csv.bz2\")) #> Rows: 32 Columns: 11 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 32 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows if (FALSE) { # Including remote paths read_csv(\"https://github.com/tidyverse/readr/raw/main/inst/extdata/mtcars.csv\") } # Read from multiple file paths at once continents <- c(\"africa\", \"americas\", \"asia\", \"europe\", \"oceania\") filepaths <- vapply( paste0(\"mini-gapminder-\", continents, \".csv\"), FUN = readr_example, FUN.VALUE = character(1) ) read_csv(filepaths, id = \"file\") #> Rows: 26 Columns: 6 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (1): country #> dbl (4): year, lifeExp, pop, gdpPercap #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 26 × 6 #> file country year lifeExp pop gdpPercap #> #> 1 /home/runner/work/_temp/Library… Algeria 1952 43.1 9.28e6 2449. #> 2 /home/runner/work/_temp/Library… Angola 1952 30.0 4.23e6 3521. #> 3 /home/runner/work/_temp/Library… Benin 1952 38.2 1.74e6 1063. #> 4 /home/runner/work/_temp/Library… Botswa… 1952 47.6 4.42e5 851. #> 5 /home/runner/work/_temp/Library… Burkin… 1952 32.0 4.47e6 543. #> 6 /home/runner/work/_temp/Library… Burundi 1952 39.0 2.45e6 339. #> 7 /home/runner/work/_temp/Library… Argent… 1952 62.5 1.79e7 5911. #> 8 /home/runner/work/_temp/Library… Bolivia 1952 40.4 2.88e6 2677. #> 9 /home/runner/work/_temp/Library… Brazil 1952 50.9 5.66e7 2109. #> 10 /home/runner/work/_temp/Library… Canada 1952 68.8 1.48e7 11367. #> # ℹ 16 more rows # Or directly from a string with `I()` read_csv(I(\"x,y\\n1,2\\n3,4\")) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x, y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x y #> #> 1 1 2 #> 2 3 4 # Column selection----------------------------------------------------------- # Pass column names or indexes directly to select them read_csv(readr_example(\"chickens.csv\"), col_select = c(chicken, eggs_laid)) #> Rows: 5 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (1): chicken #> dbl (1): eggs_laid #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 2 #> chicken eggs_laid #> #> 1 Foghorn Leghorn 0 #> 2 Chicken Little 3 #> 3 Ginger 12 #> 4 Camilla the Chicken 7 #> 5 Ernie The Giant Chicken 0 read_csv(readr_example(\"chickens.csv\"), col_select = c(1, 3:4)) #> Rows: 5 Columns: 3 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (2): chicken, motto #> dbl (1): eggs_laid #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 3 #> chicken eggs_laid motto #> #> 1 Foghorn Leghorn 0 That's a joke, ah say, that's a joke,… #> 2 Chicken Little 3 The sky is falling! #> 3 Ginger 12 Listen. We'll either die free chicken… #> 4 Camilla the Chicken 7 Bawk, buck, ba-gawk. #> 5 Ernie The Giant Chicken 0 Put Captain Solo in the cargo hold. # Or use the selection helpers read_csv( readr_example(\"chickens.csv\"), col_select = c(starts_with(\"c\"), last_col()) ) #> Rows: 5 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (2): chicken, motto #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 2 #> chicken motto #> #> 1 Foghorn Leghorn That's a joke, ah say, that's a joke, son. #> 2 Chicken Little The sky is falling! #> 3 Ginger Listen. We'll either die free chickens or we di… #> 4 Camilla the Chicken Bawk, buck, ba-gawk. #> 5 Ernie The Giant Chicken Put Captain Solo in the cargo hold. # You can also rename specific columns read_csv( readr_example(\"chickens.csv\"), col_select = c(egg_yield = eggs_laid, everything()) ) #> Rows: 5 Columns: 4 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (3): chicken, sex, motto #> dbl (1): eggs_laid #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 4 #> egg_yield chicken sex motto #> #> 1 0 Foghorn Leghorn rooster That's a joke, ah say, that's… #> 2 3 Chicken Little hen The sky is falling! #> 3 12 Ginger hen Listen. We'll either die free… #> 4 7 Camilla the Chicken hen Bawk, buck, ba-gawk. #> 5 0 Ernie The Giant Chicken rooster Put Captain Solo in the cargo… # Column types -------------------------------------------------------------- # By default, readr guesses the columns types, looking at `guess_max` rows. # You can override with a compact specification: read_csv(I(\"x,y\\n1,2\\n3,4\"), col_types = \"dc\") #> # A tibble: 2 × 2 #> x y #> #> 1 1 2 #> 2 3 4 # Or with a list of column types: read_csv(I(\"x,y\\n1,2\\n3,4\"), col_types = list(col_double(), col_character())) #> # A tibble: 2 × 2 #> x y #> #> 1 1 2 #> 2 3 4 # If there are parsing problems, you get a warning, and can extract # more details with problems() y <- read_csv(I(\"x\\n1\\n2\\nb\"), col_types = list(col_double())) #> Warning: One or more parsing issues, call `problems()` on your data frame for #> details, e.g.: #> dat <- vroom(...) #> problems(dat) y #> # A tibble: 3 × 1 #> x #> #> 1 1 #> 2 2 #> 3 NA problems(y) #> # A tibble: 1 × 5 #> row col expected actual file #> #> 1 4 1 a double b /tmp/RtmpASSHEF/file1813274ac7e1 # Column names -------------------------------------------------------------- # By default, readr duplicate name repair is noisy read_csv(I(\"x,x\\n1,2\\n3,4\")) #> New names: #> • `x` -> `x...1` #> • `x` -> `x...2` #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x...1, x...2 #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x...1 x...2 #> #> 1 1 2 #> 2 3 4 # Same default repair strategy, but quiet read_csv(I(\"x,x\\n1,2\\n3,4\"), name_repair = \"unique_quiet\") #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x...1, x...2 #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x...1 x...2 #> #> 1 1 2 #> 2 3 4 # There's also a global option that controls verbosity of name repair withr::with_options( list(rlib_name_repair_verbosity = \"quiet\"), read_csv(I(\"x,x\\n1,2\\n3,4\")) ) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x...1, x...2 #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x...1 x...2 #> #> 1 1 2 #> 2 3 4 # Or use \"minimal\" to turn off name repair read_csv(I(\"x,x\\n1,2\\n3,4\"), name_repair = \"minimal\") #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x, x #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x x #> #> 1 1 2 #> 2 3 4 # File types ---------------------------------------------------------------- read_csv(I(\"a,b\\n1.0,2.0\")) #> Rows: 1 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): a, b #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 1 × 2 #> a b #> #> 1 1 2 read_csv2(I(\"a;b\\n1,0;2,0\")) #> ℹ Using \"','\" as decimal and \"'.'\" as grouping mark. Use `read_delim()` for more control. #> Rows: 1 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \";\" #> dbl (2): a, b #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 1 × 2 #> a b #> #> 1 1 2 read_tsv(I(\"a\\tb\\n1.0\\t2.0\")) #> Rows: 1 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \"\\t\" #> dbl (2): a, b #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 1 × 2 #> a b #> #> 1 1 2 read_delim(I(\"a|b\\n1.0|2.0\"), delim = \"|\") #> Rows: 1 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \"|\" #> dbl (2): a, b #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 1 × 2 #> a b #> #> 1 1 2"},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":null,"dir":"Reference","previous_headings":"","what":"Read a delimited file by chunks — read_delim_chunked","title":"Read a delimited file by chunks — read_delim_chunked","text":"Read delimited file chunks","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read a delimited file by chunks — read_delim_chunked","text":"","code":"read_delim_chunked( file, callback, delim = NULL, chunk_size = 10000, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, col_names = TRUE, col_types = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, guess_max = chunk_size, progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE ) read_csv_chunked( file, callback, chunk_size = 10000, col_names = TRUE, col_types = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, guess_max = chunk_size, progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE ) read_csv2_chunked( file, callback, chunk_size = 10000, col_names = TRUE, col_types = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, guess_max = chunk_size, progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE ) read_tsv_chunked( file, callback, chunk_size = 10000, col_names = TRUE, col_types = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, guess_max = chunk_size, progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read a delimited file by chunks — read_delim_chunked","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. callback callback function call chunk delim Single character used separate fields within record. chunk_size number rows include chunk quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read a delimited file by chunks — read_delim_chunked","text":"number lines file can exceed maximum integer value R (~2 billion).","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read a delimited file by chunks — read_delim_chunked","text":"","code":"# Cars with 3 gears f <- function(x, pos) subset(x, gear == 3) read_csv_chunked(readr_example(\"mtcars.csv\"), DataFrameCallback$new(f), chunk_size = 5) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> # A tibble: 15 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 2 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 3 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 4 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 5 16.4 8 276. 180 3.07 4.07 17.4 0 0 3 3 #> 6 17.3 8 276. 180 3.07 3.73 17.6 0 0 3 3 #> 7 15.2 8 276. 180 3.07 3.78 18 0 0 3 3 #> 8 10.4 8 472 205 2.93 5.25 18.0 0 0 3 4 #> 9 10.4 8 460 215 3 5.42 17.8 0 0 3 4 #> 10 14.7 8 440 230 3.23 5.34 17.4 0 0 3 4 #> 11 21.5 4 120. 97 3.7 2.46 20.0 1 0 3 1 #> 12 15.5 8 318 150 2.76 3.52 16.9 0 0 3 2 #> 13 15.2 8 304 150 3.15 3.44 17.3 0 0 3 2 #> 14 13.3 8 350 245 3.73 3.84 15.4 0 0 3 4 #> 15 19.2 8 400 175 3.08 3.84 17.0 0 0 3 2"},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":null,"dir":"Reference","previous_headings":"","what":"Read/write a complete file — read_file","title":"Read/write a complete file — read_file","text":"read_file() reads complete file single object: either character vector length one, raw vector. write_file() takes single string, raw vector, writes exactly . Raw vectors useful dealing binary data, text data unknown encoding.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read/write a complete file — read_file","text":"","code":"read_file(file, locale = default_locale()) read_file_raw(file) write_file(x, file, append = FALSE, path = deprecated())"},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read/write a complete file — read_file","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. x single string, raw vector write disk. append FALSE, overwrite existing file. TRUE, append existing file. cases, file exist new file created. path Use file argument instead.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read/write a complete file — read_file","text":"read_file: length 1 character vector. read_lines_raw: raw vector.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read/write a complete file — read_file","text":"","code":"read_file(file.path(R.home(\"doc\"), \"AUTHORS\")) #> [1] \"Authors of R.\\n\\nR was initially written by Robert Gentleman and Ross Ihaka—also known as \\\"R & R\\\"\\nof the Statistics Department of the University of Auckland.\\n\\nSince mid-1997 there has been a core group with write access to the R\\nsource, currently consisting of\\n\\nDouglas Bates\\nJohn Chambers\\nPeter Dalgaard\\nRobert Gentleman\\nKurt Hornik\\nRoss Ihaka\\nTomas Kalibera\\nMichael Lawrence\\nFriedrich Leisch\\nUwe Ligges\\nThomas Lumley\\nMartin Maechler\\nSebastian Meyer\\nPaul Murrell\\nMartyn Plummer\\nBrian Ripley\\nDeepayan Sarkar\\nDuncan Temple Lang\\nLuke Tierney\\nSimon Urbanek\\n\\nplus Heiner Schwarte up to October 1999, Guido Masarotto up to June 2003,\\nStefano Iacus up to July 2014, Seth Falcon up to August 2015, Duncan Murdoch\\nup to September 2017, and Martin Morgan up to June 2021.\\n\\n\\nCurrent R-core members can be contacted via email to R-project.org\\nwith name made up by replacing spaces by dots in the name listed above.\\n\\n(The authors of code from other projects included in the R distribution\\nare listed in the COPYRIGHTS file.)\\n\" read_file_raw(file.path(R.home(\"doc\"), \"AUTHORS\")) #> [1] 41 75 74 68 6f 72 73 20 6f 66 20 52 2e 0a 0a 52 20 77 61 73 20 69 #> [23] 6e 69 74 69 61 6c 6c 79 20 77 72 69 74 74 65 6e 20 62 79 20 52 6f #> [45] 62 65 72 74 20 47 65 6e 74 6c 65 6d 61 6e 20 61 6e 64 20 52 6f 73 #> [67] 73 20 49 68 61 6b 61 e2 80 94 61 6c 73 6f 20 6b 6e 6f 77 6e 20 61 #> [89] 73 20 22 52 20 26 20 52 22 0a 6f 66 20 74 68 65 20 53 74 61 74 69 #> [111] 73 74 69 63 73 20 44 65 70 61 72 74 6d 65 6e 74 20 6f 66 20 74 68 #> [133] 65 20 55 6e 69 76 65 72 73 69 74 79 20 6f 66 20 41 75 63 6b 6c 61 #> [155] 6e 64 2e 0a 0a 53 69 6e 63 65 20 6d 69 64 2d 31 39 39 37 20 74 68 #> [177] 65 72 65 20 68 61 73 20 62 65 65 6e 20 61 20 63 6f 72 65 20 67 72 #> [199] 6f 75 70 20 77 69 74 68 20 77 72 69 74 65 20 61 63 63 65 73 73 20 #> [221] 74 6f 20 74 68 65 20 52 0a 73 6f 75 72 63 65 2c 20 63 75 72 72 65 #> [243] 6e 74 6c 79 20 63 6f 6e 73 69 73 74 69 6e 67 20 6f 66 0a 0a 44 6f #> [265] 75 67 6c 61 73 20 42 61 74 65 73 0a 4a 6f 68 6e 20 43 68 61 6d 62 #> [287] 65 72 73 0a 50 65 74 65 72 20 44 61 6c 67 61 61 72 64 0a 52 6f 62 #> [309] 65 72 74 20 47 65 6e 74 6c 65 6d 61 6e 0a 4b 75 72 74 20 48 6f 72 #> [331] 6e 69 6b 0a 52 6f 73 73 20 49 68 61 6b 61 0a 54 6f 6d 61 73 20 4b #> [353] 61 6c 69 62 65 72 61 0a 4d 69 63 68 61 65 6c 20 4c 61 77 72 65 6e #> [375] 63 65 0a 46 72 69 65 64 72 69 63 68 20 4c 65 69 73 63 68 0a 55 77 #> [397] 65 20 4c 69 67 67 65 73 0a 54 68 6f 6d 61 73 20 4c 75 6d 6c 65 79 #> [419] 0a 4d 61 72 74 69 6e 20 4d 61 65 63 68 6c 65 72 0a 53 65 62 61 73 #> [441] 74 69 61 6e 20 4d 65 79 65 72 0a 50 61 75 6c 20 4d 75 72 72 65 6c #> [463] 6c 0a 4d 61 72 74 79 6e 20 50 6c 75 6d 6d 65 72 0a 42 72 69 61 6e #> [485] 20 52 69 70 6c 65 79 0a 44 65 65 70 61 79 61 6e 20 53 61 72 6b 61 #> [507] 72 0a 44 75 6e 63 61 6e 20 54 65 6d 70 6c 65 20 4c 61 6e 67 0a 4c #> [529] 75 6b 65 20 54 69 65 72 6e 65 79 0a 53 69 6d 6f 6e 20 55 72 62 61 #> [551] 6e 65 6b 0a 0a 70 6c 75 73 20 48 65 69 6e 65 72 20 53 63 68 77 61 #> [573] 72 74 65 20 75 70 20 74 6f 20 4f 63 74 6f 62 65 72 20 31 39 39 39 #> [595] 2c 20 47 75 69 64 6f 20 4d 61 73 61 72 6f 74 74 6f 20 75 70 20 74 #> [617] 6f 20 4a 75 6e 65 20 32 30 30 33 2c 0a 53 74 65 66 61 6e 6f 20 49 #> [639] 61 63 75 73 20 75 70 20 74 6f 20 4a 75 6c 79 20 32 30 31 34 2c 20 #> [661] 53 65 74 68 20 46 61 6c 63 6f 6e 20 75 70 20 74 6f 20 41 75 67 75 #> [683] 73 74 20 32 30 31 35 2c 20 44 75 6e 63 61 6e 20 4d 75 72 64 6f 63 #> [705] 68 0a 75 70 20 74 6f 20 53 65 70 74 65 6d 62 65 72 20 32 30 31 37 #> [727] 2c 20 61 6e 64 20 4d 61 72 74 69 6e 20 4d 6f 72 67 61 6e 20 75 70 #> [749] 20 74 6f 20 4a 75 6e 65 20 32 30 32 31 2e 0a 0a 0a 43 75 72 72 65 #> [771] 6e 74 20 52 2d 63 6f 72 65 20 6d 65 6d 62 65 72 73 20 63 61 6e 20 #> [793] 62 65 20 63 6f 6e 74 61 63 74 65 64 20 76 69 61 20 65 6d 61 69 6c #> [815] 20 74 6f 20 52 2d 70 72 6f 6a 65 63 74 2e 6f 72 67 0a 77 69 74 68 #> [837] 20 6e 61 6d 65 20 6d 61 64 65 20 75 70 20 62 79 20 72 65 70 6c 61 #> [859] 63 69 6e 67 20 73 70 61 63 65 73 20 62 79 20 64 6f 74 73 20 69 6e #> [881] 20 74 68 65 20 6e 61 6d 65 20 6c 69 73 74 65 64 20 61 62 6f 76 65 #> [903] 2e 0a 0a 28 54 68 65 20 61 75 74 68 6f 72 73 20 6f 66 20 63 6f 64 #> [925] 65 20 66 72 6f 6d 20 6f 74 68 65 72 20 70 72 6f 6a 65 63 74 73 20 #> [947] 69 6e 63 6c 75 64 65 64 20 69 6e 20 74 68 65 20 52 20 64 69 73 74 #> [969] 72 69 62 75 74 69 6f 6e 0a 61 72 65 20 6c 69 73 74 65 64 20 69 6e #> [991] 20 74 68 65 20 43 4f 50 59 52 49 47 48 54 53 20 66 69 6c 65 2e 29 #> [1013] 0a tmp <- tempfile() x <- format_csv(mtcars[1:6, ]) write_file(x, tmp) identical(x, read_file(tmp)) #> [1] TRUE read_lines(I(x)) #> [1] \"mpg,cyl,disp,hp,drat,wt,qsec,vs,am,gear,carb\" #> [2] \"21,6,160,110,3.9,2.62,16.46,0,1,4,4\" #> [3] \"21,6,160,110,3.9,2.875,17.02,0,1,4,4\" #> [4] \"22.8,4,108,93,3.85,2.32,18.61,1,1,4,1\" #> [5] \"21.4,6,258,110,3.08,3.215,19.44,1,0,3,1\" #> [6] \"18.7,8,360,175,3.15,3.44,17.02,0,0,3,2\" #> [7] \"18.1,6,225,105,2.76,3.46,20.22,1,0,3,1\""},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":null,"dir":"Reference","previous_headings":"","what":"Read a fixed width file into a tibble — read_fwf","title":"Read a fixed width file into a tibble — read_fwf","text":"fixed width file can compact representation numeric data. also fast parse, every field place every line. Unfortunately, painful parse need describe length every field. Readr aims make easy possible providing number different ways describe field structure. fwf_empty() - Guesses based positions empty columns. fwf_widths() - Supply widths columns. fwf_positions() - Supply paired vectors start end positions. fwf_cols() - Supply named arguments paired start end positions column widths.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read a fixed width file into a tibble — read_fwf","text":"","code":"read_fwf( file, col_positions = fwf_empty(file, skip, n = guess_max), col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), lazy = should_read_lazy(), skip_empty_rows = TRUE ) fwf_empty( file, skip = 0, skip_empty_rows = FALSE, col_names = NULL, comment = \"\", n = 100L ) fwf_widths(widths, col_names = NULL) fwf_positions(start, end = NULL, col_names = NULL) fwf_cols(...)"},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read a fixed width file into a tibble — read_fwf","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. col_positions Column positions, created fwf_empty(), fwf_widths() fwf_positions(). read selected fields, use fwf_positions(). width last column variable (ragged fwf file), supply last end position NA. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). col_select Columns include results. can use mini-language dplyr::select() refer columns name. Use c() use one selection expression. Although usage less common, col_select also accepts numeric column index. See ?tidyselect::language full details selection language. id name column store file path. useful reading multiple input files data file paths, data collection date. NULL (default) extra column created. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. name_repair Handling column names. default behaviour ensure column names \"unique\". Various repair strategies supported: \"minimal\": name repair checks, beyond basic existence names. \"unique\" (default value): Make sure names unique empty. \"check_unique\": name repair, check unique. \"unique_quiet\": Repair unique strategy, quietly. \"universal\": Make names unique syntactic. \"universal_quiet\": Repair universal strategy, quietly. function: Apply custom name repair (e.g., name_repair = make.names names style base R). purrr-style anonymous function, see rlang::as_function(). argument passed repair vctrs::vec_as_names(). See details terms strategies used enforce . num_threads number processing threads use initial parsing lazy reading data. data contains newlines within fields parser automatically detect fall back using one thread . However know file newlines within quoted fields safest set num_threads = 1 explicitly. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. lazy Read values lazily? default, FALSE, special considerations reading file lazily tripped users. Specifically, things get tricky reading writing back file. , general, lazy reading (lazy = TRUE) many benefits, especially interactive use downstream work involves subset rows columns. Learn should_read_lazy() documentation altrep argument vroom::vroom(). skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. col_names Either NULL, character vector column names. n Number lines tokenizer read determine file structure. default set 100. widths Width field. Use NA width last field reading ragged fwf file. start, end Starting ending (inclusive) positions field. Use NA last end field reading ragged fwf file. ... first element data frame, must numeric columns either one two rows. column names variable names. column values variable widths length one vector, length two, variable start end positions. elements ... used construct data frame two rows .","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":"second-edition-changes","dir":"Reference","previous_headings":"","what":"Second edition changes","title":"Read a fixed width file into a tibble — read_fwf","text":"Comments longer looked anywhere file. now ignored start line.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read a fixed width file into a tibble — read_fwf","text":"","code":"fwf_sample <- readr_example(\"fwf-sample.txt\") writeLines(read_lines(fwf_sample)) #> John Smith WA 418-Y11-4111 #> Mary Hartford CA 319-Z19-4341 #> Evan Nolan IL 219-532-c301 # You can specify column positions in several ways: # 1. Guess based on position of empty columns read_fwf(fwf_sample, fwf_empty(fwf_sample, col_names = c(\"first\", \"last\", \"state\", \"ssn\"))) #> Rows: 3 Columns: 4 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (4): first, last, state, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 4 #> first last state ssn #> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301 # 2. A vector of field widths read_fwf(fwf_sample, fwf_widths(c(20, 10, 12), c(\"name\", \"state\", \"ssn\"))) #> Rows: 3 Columns: 3 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (3): name, state, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 3 #> name state ssn #> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301 # 3. Paired vectors of start and end positions read_fwf(fwf_sample, fwf_positions(c(1, 30), c(20, 42), c(\"name\", \"ssn\"))) #> Rows: 3 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (2): name, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 2 #> name ssn #> #> 1 John Smith 418-Y11-4111 #> 2 Mary Hartford 319-Z19-4341 #> 3 Evan Nolan 219-532-c301 # 4. Named arguments with start and end positions read_fwf(fwf_sample, fwf_cols(name = c(1, 20), ssn = c(30, 42))) #> Rows: 3 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (2): name, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 2 #> name ssn #> #> 1 John Smith 418-Y11-4111 #> 2 Mary Hartford 319-Z19-4341 #> 3 Evan Nolan 219-532-c301 # 5. Named arguments with column widths read_fwf(fwf_sample, fwf_cols(name = 20, state = 10, ssn = 12)) #> Rows: 3 Columns: 3 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (3): name, state, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 3 #> name state ssn #> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301"},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":null,"dir":"Reference","previous_headings":"","what":"Read/write lines to/from a file — read_lines","title":"Read/write lines to/from a file — read_lines","text":"read_lines() reads n_max lines file. New lines included output. read_lines_raw() produces list raw vectors, useful handling data unknown encoding. write_lines() takes character vector list raw vectors, appending new line entry.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read/write lines to/from a file — read_lines","text":"","code":"read_lines( file, skip = 0, skip_empty_rows = FALSE, n_max = Inf, locale = default_locale(), na = character(), lazy = should_read_lazy(), num_threads = readr_threads(), progress = show_progress() ) read_lines_raw( file, skip = 0, n_max = -1L, num_threads = readr_threads(), progress = show_progress() ) write_lines( x, file, sep = \"\\n\", na = \"NA\", append = FALSE, num_threads = readr_threads(), path = deprecated() )"},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read/write lines to/from a file — read_lines","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. skip Number lines skip reading data. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. n_max Number lines read. n_max -1, lines file read. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. lazy Read values lazily? default, FALSE, special considerations reading file lazily tripped users. Specifically, things get tricky reading writing back file. , general, lazy reading (lazy = TRUE) many benefits, especially interactive use downstream work involves subset rows columns. Learn should_read_lazy() documentation altrep argument vroom::vroom(). num_threads number processing threads use initial parsing lazy reading data. data contains newlines within fields parser automatically detect fall back using one thread . However know file newlines within quoted fields safest set num_threads = 1 explicitly. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. x character vector list raw vectors write disk. sep line separator. Defaults \\\\n, commonly used POSIX systems like macOS linux. native windows (CRLF) separators use \\\\r\\\\n. append FALSE, overwrite existing file. TRUE, append existing file. cases, file exist new file created. path Use file argument instead.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read/write lines to/from a file — read_lines","text":"read_lines(): character vector one element line. read_lines_raw(): list containing raw vector line. write_lines() returns x, invisibly.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read/write lines to/from a file — read_lines","text":"","code":"read_lines(file.path(R.home(\"doc\"), \"AUTHORS\"), n_max = 10) #> [1] \"Authors of R.\" #> [2] \"\" #> [3] \"R was initially written by Robert Gentleman and Ross Ihaka—also known as \\\"R & R\\\"\" #> [4] \"of the Statistics Department of the University of Auckland.\" #> [5] \"\" #> [6] \"Since mid-1997 there has been a core group with write access to the R\" #> [7] \"source, currently consisting of\" #> [8] \"\" #> [9] \"Douglas Bates\" #> [10] \"John Chambers\" read_lines_raw(file.path(R.home(\"doc\"), \"AUTHORS\"), n_max = 10) #> [[1]] #> [1] 41 75 74 68 6f 72 73 20 6f 66 20 52 2e #> #> [[2]] #> raw(0) #> #> [[3]] #> [1] 52 20 77 61 73 20 69 6e 69 74 69 61 6c 6c 79 20 77 72 69 74 74 65 6e #> [24] 20 62 79 20 52 6f 62 65 72 74 20 47 65 6e 74 6c 65 6d 61 6e 20 61 6e #> [47] 64 20 52 6f 73 73 20 49 68 61 6b 61 e2 80 94 61 6c 73 6f 20 6b 6e 6f #> [70] 77 6e 20 61 73 20 22 52 20 26 20 52 22 #> #> [[4]] #> [1] 6f 66 20 74 68 65 20 53 74 61 74 69 73 74 69 63 73 20 44 65 70 61 72 #> [24] 74 6d 65 6e 74 20 6f 66 20 74 68 65 20 55 6e 69 76 65 72 73 69 74 79 #> [47] 20 6f 66 20 41 75 63 6b 6c 61 6e 64 2e #> #> [[5]] #> raw(0) #> #> [[6]] #> [1] 53 69 6e 63 65 20 6d 69 64 2d 31 39 39 37 20 74 68 65 72 65 20 68 61 #> [24] 73 20 62 65 65 6e 20 61 20 63 6f 72 65 20 67 72 6f 75 70 20 77 69 74 #> [47] 68 20 77 72 69 74 65 20 61 63 63 65 73 73 20 74 6f 20 74 68 65 20 52 #> #> [[7]] #> [1] 73 6f 75 72 63 65 2c 20 63 75 72 72 65 6e 74 6c 79 20 63 6f 6e 73 69 #> [24] 73 74 69 6e 67 20 6f 66 #> #> [[8]] #> raw(0) #> #> [[9]] #> [1] 44 6f 75 67 6c 61 73 20 42 61 74 65 73 #> #> [[10]] #> [1] 4a 6f 68 6e 20 43 68 61 6d 62 65 72 73 #> tmp <- tempfile() write_lines(rownames(mtcars), tmp) read_lines(tmp, lazy = FALSE) #> [1] \"Mazda RX4\" \"Mazda RX4 Wag\" \"Datsun 710\" #> [4] \"Hornet 4 Drive\" \"Hornet Sportabout\" \"Valiant\" #> [7] \"Duster 360\" \"Merc 240D\" \"Merc 230\" #> [10] \"Merc 280\" \"Merc 280C\" \"Merc 450SE\" #> [13] \"Merc 450SL\" \"Merc 450SLC\" \"Cadillac Fleetwood\" #> [16] \"Lincoln Continental\" \"Chrysler Imperial\" \"Fiat 128\" #> [19] \"Honda Civic\" \"Toyota Corolla\" \"Toyota Corona\" #> [22] \"Dodge Challenger\" \"AMC Javelin\" \"Camaro Z28\" #> [25] \"Pontiac Firebird\" \"Fiat X1-9\" \"Porsche 914-2\" #> [28] \"Lotus Europa\" \"Ford Pantera L\" \"Ferrari Dino\" #> [31] \"Maserati Bora\" \"Volvo 142E\" read_file(tmp) # note trailing \\n #> [1] \"Mazda RX4\\nMazda RX4 Wag\\nDatsun 710\\nHornet 4 Drive\\nHornet Sportabout\\nValiant\\nDuster 360\\nMerc 240D\\nMerc 230\\nMerc 280\\nMerc 280C\\nMerc 450SE\\nMerc 450SL\\nMerc 450SLC\\nCadillac Fleetwood\\nLincoln Continental\\nChrysler Imperial\\nFiat 128\\nHonda Civic\\nToyota Corolla\\nToyota Corona\\nDodge Challenger\\nAMC Javelin\\nCamaro Z28\\nPontiac Firebird\\nFiat X1-9\\nPorsche 914-2\\nLotus Europa\\nFord Pantera L\\nFerrari Dino\\nMaserati Bora\\nVolvo 142E\\n\" write_lines(airquality$Ozone, tmp, na = \"-1\") read_lines(tmp) #> [1] \"41\" \"36\" \"12\" \"18\" \"-1\" \"28\" \"23\" \"19\" \"8\" \"-1\" \"7\" #> [12] \"16\" \"11\" \"14\" \"18\" \"14\" \"34\" \"6\" \"30\" \"11\" \"1\" \"11\" #> [23] \"4\" \"32\" \"-1\" \"-1\" \"-1\" \"23\" \"45\" \"115\" \"37\" \"-1\" \"-1\" #> [34] \"-1\" \"-1\" \"-1\" \"-1\" \"29\" \"-1\" \"71\" \"39\" \"-1\" \"-1\" \"23\" #> [45] \"-1\" \"-1\" \"21\" \"37\" \"20\" \"12\" \"13\" \"-1\" \"-1\" \"-1\" \"-1\" #> [56] \"-1\" \"-1\" \"-1\" \"-1\" \"-1\" \"-1\" \"135\" \"49\" \"32\" \"-1\" \"64\" #> [67] \"40\" \"77\" \"97\" \"97\" \"85\" \"-1\" \"10\" \"27\" \"-1\" \"7\" \"48\" #> [78] \"35\" \"61\" \"79\" \"63\" \"16\" \"-1\" \"-1\" \"80\" \"108\" \"20\" \"52\" #> [89] \"82\" \"50\" \"64\" \"59\" \"39\" \"9\" \"16\" \"78\" \"35\" \"66\" \"122\" #> [100] \"89\" \"110\" \"-1\" \"-1\" \"44\" \"28\" \"65\" \"-1\" \"22\" \"59\" \"23\" #> [111] \"31\" \"44\" \"21\" \"9\" \"-1\" \"45\" \"168\" \"73\" \"-1\" \"76\" \"118\" #> [122] \"84\" \"85\" \"96\" \"78\" \"73\" \"91\" \"47\" \"32\" \"20\" \"23\" \"21\" #> [133] \"24\" \"44\" \"21\" \"28\" \"9\" \"13\" \"46\" \"18\" \"13\" \"24\" \"16\" #> [144] \"13\" \"23\" \"36\" \"7\" \"14\" \"30\" \"-1\" \"14\" \"18\" \"20\""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines_chunked.html","id":null,"dir":"Reference","previous_headings":"","what":"Read lines from a file or string by chunk. — read_lines_chunked","title":"Read lines from a file or string by chunk. — read_lines_chunked","text":"Read lines file string chunk.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines_chunked.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read lines from a file or string by chunk. — read_lines_chunked","text":"","code":"read_lines_chunked( file, callback, chunk_size = 10000, skip = 0, locale = default_locale(), na = character(), progress = show_progress() ) read_lines_raw_chunked( file, callback, chunk_size = 10000, skip = 0, progress = show_progress() )"},{"path":"https://readr.tidyverse.org/dev/reference/read_lines_chunked.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read lines from a file or string by chunk. — read_lines_chunked","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. callback callback function call chunk chunk_size number rows include chunk skip Number lines skip reading data. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/read_log.html","id":null,"dir":"Reference","previous_headings":"","what":"Read common/combined log file into a tibble — read_log","title":"Read common/combined log file into a tibble — read_log","text":"fairly standard format log files - uses quotes square brackets quoting, may literal quotes embedded quoted string. dash, \"-\", used missing values.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_log.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read common/combined log file into a tibble — read_log","text":"","code":"read_log( file, col_names = FALSE, col_types = NULL, trim_ws = TRUE, skip = 0, n_max = Inf, show_col_types = should_show_types(), progress = show_progress() )"},{"path":"https://readr.tidyverse.org/dev/reference/read_log.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read common/combined log file into a tibble — read_log","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. n_max Maximum number lines read. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_log.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read common/combined log file into a tibble — read_log","text":"","code":"read_log(readr_example(\"example.log\")) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> X1 = col_character(), #> X2 = col_logical(), #> X3 = col_character(), #> X4 = col_character(), #> X5 = col_character(), #> X6 = col_double(), #> X7 = col_double() #> ) #> # A tibble: 2 × 7 #> X1 X2 X3 X4 X5 X6 X7 #> #> 1 172.21.13.45 NA \"Microsoft\\\\JohnDoe\" 08/Apr/2001:1… GET … 200 3401 #> 2 127.0.0.1 NA \"frank\" 10/Oct/2000:1… GET … 200 2326"},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":null,"dir":"Reference","previous_headings":"","what":"Read/write RDS files. — read_rds","title":"Read/write RDS files. — read_rds","text":"Consistent wrapper around saveRDS() readRDS(). write_rds() compress default space generally cheaper time.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read/write RDS files. — read_rds","text":"","code":"read_rds(file, refhook = NULL) write_rds( x, file, compress = c(\"none\", \"gz\", \"bz2\", \"xz\"), version = 2, refhook = NULL, text = FALSE, path = deprecated(), ... )"},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read/write RDS files. — read_rds","text":"file file path read /write . refhook function handle reference objects. x R object write serialise. compress Compression method use: \"none\", \"gz\" ,\"bz\", \"xz\". version Serialization format version used. default value 2 compatible R versions prior 3.5.0. See base::saveRDS() details. text TRUE text representation used, otherwise binary representation used. path Use file argument instead. ... Additional arguments connection function. example, control space-time trade-different compression methods compression. See connections() details.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read/write RDS files. — read_rds","text":"write_rds() returns x, invisibly.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read/write RDS files. — read_rds","text":"","code":"temp <- tempfile() write_rds(mtcars, temp) read_rds(temp) #> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 if (FALSE) { write_rds(mtcars, \"compressed_mtc.rds\", \"xz\", compression = 9L) }"},{"path":"https://readr.tidyverse.org/dev/reference/read_table.html","id":null,"dir":"Reference","previous_headings":"","what":"Read whitespace-separated columns into a tibble — read_table","title":"Read whitespace-separated columns into a tibble — read_table","text":"read_table() designed read type textual data column separated one () columns space. read_table() like read.table(), allows number whitespace characters columns, lines can different lengths. spec_table() returns column specifications rather data frame.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_table.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read whitespace-separated columns into a tibble — read_table","text":"","code":"read_table( file, col_names = TRUE, col_types = NULL, locale = default_locale(), na = \"NA\", skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress(), comment = \"\", show_col_types = should_show_types(), skip_empty_rows = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/read_table.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read whitespace-separated columns into a tibble — read_table","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. skip Number lines skip reading data. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. comment string used identify comments. text comment characters silently ignored. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/read_table.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read whitespace-separated columns into a tibble — read_table","text":"","code":"ws <- readr_example(\"whitespace-sample.txt\") writeLines(read_lines(ws)) #> first last state phone #> John Smith WA 418-Y11-4111 #> Mary Hartford CA 319-Z19-4341 #> Evan Nolan IL 219-532-c301 read_table(ws) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> first = col_character(), #> last = col_character(), #> state = col_character(), #> phone = col_character() #> ) #> # A tibble: 3 × 4 #> first last state phone #> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301"},{"path":"https://readr.tidyverse.org/dev/reference/read_table2.html","id":null,"dir":"Reference","previous_headings":"","what":"Read whitespace-separated columns into a tibble — read_table2","title":"Read whitespace-separated columns into a tibble — read_table2","text":"function deprecated renamed read_table() removed old read_table function, strict cases analogous just using read_fwf().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_table2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read whitespace-separated columns into a tibble — read_table2","text":"","code":"read_table2( file, col_names = TRUE, col_types = NULL, locale = default_locale(), na = \"NA\", skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress(), comment = \"\", skip_empty_rows = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/readr-package.html","id":null,"dir":"Reference","previous_headings":"","what":"readr: Read Rectangular Text Data — readr-package","title":"readr: Read Rectangular Text Data — readr-package","text":"goal 'readr' provide fast friendly way read rectangular data (like 'csv', 'tsv', 'fwf'). designed flexibly parse many types data found wild, still cleanly failing data unexpectedly changes.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/readr-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"readr: Read Rectangular Text Data — readr-package","text":"Maintainer: Jennifer Bryan jenny@posit.co (ORCID) Authors: Hadley Wickham hadley@posit.co Jim Hester contributors: Romain Francois [contributor] Shelby Bearrows [contributor] Posit Software, PBC [copyright holder, funder] https://github.com/mandreyel/ (mio library) [copyright holder] Jukka Jylänki (grisu3 implementation) [contributor, copyright holder] Mikkel Jørgensen (grisu3 implementation) [contributor, copyright holder]","code":""},{"path":"https://readr.tidyverse.org/dev/reference/readr_example.html","id":null,"dir":"Reference","previous_headings":"","what":"Get path to readr example — readr_example","title":"Get path to readr example — readr_example","text":"readr comes bundled number sample files inst/extdata directory. function make easy access","code":""},{"path":"https://readr.tidyverse.org/dev/reference/readr_example.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get path to readr example — readr_example","text":"","code":"readr_example(file = NULL)"},{"path":"https://readr.tidyverse.org/dev/reference/readr_example.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get path to readr example — readr_example","text":"file Name file. NULL, example files listed.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/readr_example.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get path to readr example — readr_example","text":"","code":"readr_example() #> [1] \"challenge.csv\" \"chickens.csv\" #> [3] \"epa78.txt\" \"example.log\" #> [5] \"fwf-sample.txt\" \"massey-rating.txt\" #> [7] \"mini-gapminder-africa.csv\" \"mini-gapminder-americas.csv\" #> [9] \"mini-gapminder-asia.csv\" \"mini-gapminder-europe.csv\" #> [11] \"mini-gapminder-oceania.csv\" \"mtcars.csv\" #> [13] \"mtcars.csv.bz2\" \"mtcars.csv.zip\" #> [15] \"whitespace-sample.txt\" readr_example(\"challenge.csv\") #> [1] \"/home/runner/work/_temp/Library/readr/extdata/challenge.csv\""},{"path":"https://readr.tidyverse.org/dev/reference/readr_threads.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine how many threads readr should use when processing — readr_threads","title":"Determine how many threads readr should use when processing — readr_threads","text":"number threads returned can set global option readr.num_threads environment variable VROOM_THREADS value parallel::detectCores()","code":""},{"path":"https://readr.tidyverse.org/dev/reference/readr_threads.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine how many threads readr should use when processing — readr_threads","text":"","code":"readr_threads()"},{"path":"https://readr.tidyverse.org/dev/reference/should_read_lazy.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine whether to read a file lazily — should_read_lazy","title":"Determine whether to read a file lazily — should_read_lazy","text":"function consults option readr.read_lazy figure whether lazy reading . option unset, default FALSE, meaning readr read files eagerly, lazily. want use option express preference lazy reading, : Typically, one use option control lazy reading session, file, user level. lazy argument functions like read_csv() can used control laziness individual call.","code":"options(readr.read_lazy = TRUE)"},{"path":"https://readr.tidyverse.org/dev/reference/should_read_lazy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine whether to read a file lazily — should_read_lazy","text":"","code":"should_read_lazy()"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/should_show_types.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine whether column types should be shown — should_show_types","title":"Determine whether column types should be shown — should_show_types","text":"Wrapper around getOption(\"readr.show_col_types\") implements fall back logic option unset. returns: TRUE option set TRUE FALSE option set FALSE FALSE option unset appear running tests NULL otherwise, case caller determines whether show column types based context, e.g. whether show_col_types actual col_types explicitly specified","code":""},{"path":"https://readr.tidyverse.org/dev/reference/should_show_types.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine whether column types should be shown — should_show_types","text":"","code":"should_show_types()"},{"path":"https://readr.tidyverse.org/dev/reference/show_progress.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine whether progress bars should be shown — show_progress","title":"Determine whether progress bars should be shown — show_progress","text":"default, readr shows progress bars. However, progress reporting suppressed following conditions hold: bar explicitly disabled setting options(readr.show_progress = FALSE). code run non-interactive session, determined rlang::is_interactive(). code run RStudio notebook chunk, determined getOption(\"rstudio.notebook.executing\").","code":""},{"path":"https://readr.tidyverse.org/dev/reference/show_progress.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine whether progress bars should be shown — show_progress","text":"","code":"show_progress()"},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":null,"dir":"Reference","previous_headings":"","what":"Examine the column specifications for a data frame — cols_condense","title":"Examine the column specifications for a data frame — cols_condense","text":"cols_condense() takes spec object condenses definition setting default column type frequent type listing columns different type. spec() extracts full column specification tibble created readr.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Examine the column specifications for a data frame — cols_condense","text":"","code":"cols_condense(x) spec(x)"},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Examine the column specifications for a data frame — cols_condense","text":"x data frame object extract ","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Examine the column specifications for a data frame — cols_condense","text":"col_spec object.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Examine the column specifications for a data frame — cols_condense","text":"","code":"df <- read_csv(readr_example(\"mtcars.csv\")) #> Rows: 32 Columns: 11 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. s <- spec(df) s #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) cols_condense(s) #> cols( #> .default = col_double() #> )"},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a column specification — spec_delim","title":"Generate a column specification — spec_delim","text":"printed, first 20 columns printed default. override, set options(readr.num_columns) can used modify (value 0 turns printing).","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a column specification — spec_delim","text":"","code":"spec_delim( file, delim = NULL, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, col_names = TRUE, col_types = list(), col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, n_max = 0, guess_max = 1000, name_repair = \"unique\", num_threads = readr_threads(), progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) spec_csv( file, col_names = TRUE, col_types = list(), col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = 0, guess_max = 1000, name_repair = \"unique\", num_threads = readr_threads(), progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) spec_csv2( file, col_names = TRUE, col_types = list(), col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = 0, guess_max = 1000, progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) spec_tsv( file, col_names = TRUE, col_types = list(), col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = 0, guess_max = 1000, progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) spec_table( file, col_names = TRUE, col_types = list(), locale = default_locale(), na = \"NA\", skip = 0, n_max = 0, guess_max = 1000, progress = show_progress(), comment = \"\", show_col_types = should_show_types(), skip_empty_rows = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a column specification — spec_delim","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. delim Single character used separate fields within record. quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). col_select Columns include results. can use mini-language dplyr::select() refer columns name. Use c() use one selection expression. Although usage less common, col_select also accepts numeric column index. See ?tidyselect::language full details selection language. id name column store file path. useful reading multiple input files data file paths, data collection date. NULL (default) extra column created. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. name_repair Handling column names. default behaviour ensure column names \"unique\". Various repair strategies supported: \"minimal\": name repair checks, beyond basic existence names. \"unique\" (default value): Make sure names unique empty. \"check_unique\": name repair, check unique. \"unique_quiet\": Repair unique strategy, quietly. \"universal\": Make names unique syntactic. \"universal_quiet\": Repair universal strategy, quietly. function: Apply custom name repair (e.g., name_repair = make.names names style base R). purrr-style anonymous function, see rlang::as_function(). argument passed repair vctrs::vec_as_names(). See details terms strategies used enforce . num_threads number processing threads use initial parsing lazy reading data. data contains newlines within fields parser automatically detect fall back using one thread . However know file newlines within quoted fields safest set num_threads = 1 explicitly. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. lazy Read values lazily? default, FALSE, special considerations reading file lazily tripped users. Specifically, things get tricky reading writing back file. , general, lazy reading (lazy = TRUE) many benefits, especially interactive use downstream work involves subset rows columns. Learn should_read_lazy() documentation altrep argument vroom::vroom().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a column specification — spec_delim","text":"col_spec generated file.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a column specification — spec_delim","text":"","code":"# Input sources ------------------------------------------------------------- # Retrieve specs from a path spec_csv(system.file(\"extdata/mtcars.csv\", package = \"readr\")) #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) spec_csv(system.file(\"extdata/mtcars.csv.zip\", package = \"readr\")) #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) # Or directly from a string (must contain a newline) spec_csv(I(\"x,y\\n1,2\\n3,4\")) #> cols( #> x = col_double(), #> y = col_double() #> ) # Column types -------------------------------------------------------------- # By default, readr guesses the columns types, looking at 1000 rows # throughout the file. # You can specify the number of rows used with guess_max. spec_csv(system.file(\"extdata/mtcars.csv\", package = \"readr\"), guess_max = 20) #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> )"},{"path":"https://readr.tidyverse.org/dev/reference/tokenize.html","id":null,"dir":"Reference","previous_headings":"","what":"Tokenize a file/string. — tokenize","title":"Tokenize a file/string. — tokenize","text":"Turns input character vector. Usually tokenization done purely C++, never exposed R (requires copy). function useful testing, file parse correctly want see underlying tokens.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/tokenize.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tokenize a file/string. — tokenize","text":"","code":"tokenize(file, tokenizer = tokenizer_csv(), skip = 0, n_max = -1L)"},{"path":"https://readr.tidyverse.org/dev/reference/tokenize.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tokenize a file/string. — tokenize","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. tokenizer tokenizer specification. skip Number lines skip reading data. n_max Optionally, maximum number rows tokenize.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/tokenize.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tokenize a file/string. — tokenize","text":"","code":"tokenize(\"1,2\\n3,4,5\\n\\n6\") #> [[1]] #> [1] \"1\" \"2\" #> #> [[2]] #> [1] \"3\" \"4\" \"5\" #> #> [[3]] #> [1] \"6\" #> # Only tokenize first two lines tokenize(\"1,2\\n3,4,5\\n\\n6\", n = 2) #> [[1]] #> [1] \"1\" \"2\" #> #> [[2]] #> [1] \"3\" \"4\" \"5\" #>"},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":null,"dir":"Reference","previous_headings":"","what":"Re-convert character columns in existing data frame — type_convert","title":"Re-convert character columns in existing data frame — type_convert","text":"useful need manual munging - can read columns character, clean (e.g.) regular expressions let readr take another stab parsing . name homage base utils::type.convert().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Re-convert character columns in existing data frame — type_convert","text":"","code":"type_convert( df, col_types = NULL, na = c(\"\", \"NA\"), trim_ws = TRUE, locale = default_locale(), guess_integer = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Re-convert character columns in existing data frame — type_convert","text":"df data frame. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types imputed using rows. na Character vector strings interpret missing values. Set option character() indicate missing values. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. guess_integer TRUE, guess integer types whole numbers, FALSE guess numeric type numbers.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Re-convert character columns in existing data frame — type_convert","text":"type_convert() removes 'spec' attribute, likely modifies column data types. (see spec() information column specifications).","code":""},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Re-convert character columns in existing data frame — type_convert","text":"","code":"df <- data.frame( x = as.character(runif(10)), y = as.character(sample(10)), stringsAsFactors = FALSE ) str(df) #> 'data.frame':\t10 obs. of 2 variables: #> $ x: chr \"0.814958464819938\" \"0.455838981084526\" \"0.568225354654714\" \"0.0281991616357118\" ... #> $ y: chr \"8\" \"4\" \"9\" \"5\" ... str(type_convert(df)) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> x = col_double(), #> y = col_double() #> ) #> 'data.frame':\t10 obs. of 2 variables: #> $ x: num 0.815 0.4558 0.5682 0.0282 0.5738 ... #> $ y: num 8 4 9 5 2 10 3 6 1 7 df <- data.frame(x = c(\"NA\", \"10\"), stringsAsFactors = FALSE) str(type_convert(df)) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> x = col_double() #> ) #> 'data.frame':\t2 obs. of 1 variable: #> $ x: num NA 10 # Type convert can be used to infer types from an entire dataset # first read the data as character data <- read_csv(readr_example(\"mtcars.csv\"), col_types = list(.default = col_character()) ) str(data) #> spc_tbl_ [32 × 11] (S3: spec_tbl_df/tbl_df/tbl/data.frame) #> $ mpg : chr [1:32] \"21\" \"21\" \"22.8\" \"21.4\" ... #> $ cyl : chr [1:32] \"6\" \"6\" \"4\" \"6\" ... #> $ disp: chr [1:32] \"160\" \"160\" \"108\" \"258\" ... #> $ hp : chr [1:32] \"110\" \"110\" \"93\" \"110\" ... #> $ drat: chr [1:32] \"3.9\" \"3.9\" \"3.85\" \"3.08\" ... #> $ wt : chr [1:32] \"2.62\" \"2.875\" \"2.32\" \"3.215\" ... #> $ qsec: chr [1:32] \"16.46\" \"17.02\" \"18.61\" \"19.44\" ... #> $ vs : chr [1:32] \"0\" \"0\" \"1\" \"1\" ... #> $ am : chr [1:32] \"1\" \"1\" \"1\" \"0\" ... #> $ gear: chr [1:32] \"4\" \"4\" \"4\" \"3\" ... #> $ carb: chr [1:32] \"4\" \"4\" \"1\" \"1\" ... #> - attr(*, \"spec\")= #> .. cols( #> .. .default = col_character(), #> .. mpg = col_character(), #> .. cyl = col_character(), #> .. disp = col_character(), #> .. hp = col_character(), #> .. drat = col_character(), #> .. wt = col_character(), #> .. qsec = col_character(), #> .. vs = col_character(), #> .. am = col_character(), #> .. gear = col_character(), #> .. carb = col_character() #> .. ) #> - attr(*, \"problems\")= # Then convert it with type_convert type_convert(data) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> # A tibble: 32 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows"},{"path":"https://readr.tidyverse.org/dev/reference/with_edition.html","id":null,"dir":"Reference","previous_headings":"","what":"Temporarily change the active readr edition — with_edition","title":"Temporarily change the active readr edition — with_edition","text":"with_edition() allows change active edition readr given block code. local_edition() allows change active edition readr end current function file.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/with_edition.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Temporarily change the active readr edition — with_edition","text":"","code":"with_edition(edition, code) local_edition(edition, env = parent.frame())"},{"path":"https://readr.tidyverse.org/dev/reference/with_edition.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Temporarily change the active readr edition — with_edition","text":"edition single integer, 1 2. code Code run changed edition. env Environment controls scope changes. expert use .","code":""},{"path":"https://readr.tidyverse.org/dev/reference/with_edition.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Temporarily change the active readr edition — with_edition","text":"","code":"with_edition(1, edition_get()) #> [1] 1 with_edition(2, edition_get()) #> [1] 2 # readr 1e and 2e behave differently when input rows have different number # number of fields with_edition(1, read_csv(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\"))) #> Warning: 1 parsing failure. #> row col expected actual file #> 1 -- 3 columns 2 columns literal data #> # A tibble: 2 × 3 #> X Y Z #> #> 1 1 2 NA #> 2 3 4 5 with_edition(2, read_csv(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\"))) #> Warning: One or more parsing issues, call `problems()` on your data frame for #> details, e.g.: #> dat <- vroom(...) #> problems(dat) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): X #> num (1): Y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> X Y #> #> 1 1 2 #> 2 3 45 # local_edition() applies in a specific scope, for example, inside a function read_csv_1e <- function(...) { local_edition(1) read_csv(...) } read_csv(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\")) # 2e behaviour #> Warning: One or more parsing issues, call `problems()` on your data frame for #> details, e.g.: #> dat <- vroom(...) #> problems(dat) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): X #> num (1): Y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> X Y #> #> 1 1 2 #> 2 3 45 read_csv_1e(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\")) # 1e behaviour #> Warning: 1 parsing failure. #> row col expected actual file #> 1 -- 3 columns 2 columns literal data #> # A tibble: 2 × 3 #> X Y Z #> #> 1 1 2 NA #> 2 3 4 5 read_csv(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\")) # 2e behaviour #> Warning: One or more parsing issues, call `problems()` on your data frame for #> details, e.g.: #> dat <- vroom(...) #> problems(dat) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): X #> num (1): Y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> X Y #> #> 1 1 2 #> 2 3 45"},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Write a data frame to a delimited file — write_delim","title":"Write a data frame to a delimited file — write_delim","text":"write_*() family functions improvement analogous function write.csv() approximately twice fast. Unlike write.csv(), functions include row names column written file. generic function, output_column(), applied variable coerce columns suitable output.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Write a data frame to a delimited file — write_delim","text":"","code":"write_delim( x, file, delim = \" \", na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_csv( x, file, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_csv2( x, file, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_excel_csv( x, file, na = \"NA\", append = FALSE, col_names = !append, delim = \",\", quote = \"all\", escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_excel_csv2( x, file, na = \"NA\", append = FALSE, col_names = !append, delim = \";\", quote = \"all\", escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_tsv( x, file, na = \"NA\", append = FALSE, col_names = !append, quote = \"none\", escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() )"},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Write a data frame to a delimited file — write_delim","text":"x data frame tibble write disk. file File connection write . delim Delimiter used separate values. Defaults \" \" write_delim(), \",\" write_excel_csv() \";\" write_excel_csv2(). Must single character. na String used missing values. Defaults NA. Missing values never quoted; strings value na always quoted. append FALSE, overwrite existing file. TRUE, append existing file. cases, file exist new file created. col_names FALSE, column names included top file. TRUE, column names included. specified, col_names take opposite value given append. quote handle fields contain characters need quoted. needed - Values quoted needed: contain delimiter, quote, newline. - Quote fields. none - Never quote fields. escape type escape use quotes data. double - quotes escaped doubling . backslash - quotes escaped preceding backslash. none - quotes escaped. eol end line character use. commonly either \"\\n\" Unix style newlines, \"\\r\\n\" Windows style newlines. num_threads Number threads use reading materializing vectors. data contains newlines within fields parser automatically forced use single thread . progress Display progress bar? default display interactive session knitting document. display updated every 50,000 values display estimated reading time 5 seconds . automatic progress bar can disabled setting option readr.show_progress FALSE. path Use file argument instead. quote_escape Use escape argument instead.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Write a data frame to a delimited file — write_delim","text":"write_*() returns input x invisibly.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"output","dir":"Reference","previous_headings":"","what":"Output","title":"Write a data frame to a delimited file — write_delim","text":"Factors coerced character. Doubles formatted decimal string using grisu3 algorithm. POSIXct values formatted ISO8601 UTC timezone Note: POSIXct objects local non-UTC timezones converted UTC time writing. columns encoded UTF-8. write_excel_csv() write_excel_csv2() also include UTF-8 Byte order mark indicates Excel csv UTF-8 encoded. write_excel_csv2() write_csv2 created allow users different locale settings save .csv files using default settings (e.g. ; column separator , decimal separator). common European countries. Values quoted contain comma, quote newline. write_*() functions automatically compress outputs appropriate extension given. Three extensions currently supported: .gz gzip compression, .bz2 bzip2 compression .xz lzma compression. See examples information.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Write a data frame to a delimited file — write_delim","text":"Florian Loitsch, Printing Floating-Point Numbers Quickly Accurately Integers, PLDI '10, http://www.cs.tufts.edu/~nr/cs257/archive/florian-loitsch/printf.pdf","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Write a data frame to a delimited file — write_delim","text":"","code":"# \\dontshow{ .old_wd <- setwd(tempdir()) # } # If only a file name is specified, write_()* will write # the file to the current working directory. write_csv(mtcars, \"mtcars.csv\") write_tsv(mtcars, \"mtcars.tsv\") # If you add an extension to the file name, write_()* will # automatically compress the output. write_tsv(mtcars, \"mtcars.tsv.gz\") write_tsv(mtcars, \"mtcars.tsv.bz2\") write_tsv(mtcars, \"mtcars.tsv.xz\") # \\dontshow{ setwd(.old_wd) # }"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-development-version","dir":"Changelog","previous_headings":"","what":"readr (development version)","title":"readr (development version)","text":"major user-facing changes. Patch release housekeeping changes internal changes requested CRAN around format specification compiled code.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-214","dir":"Changelog","previous_headings":"","what":"readr 2.1.4","title":"readr 2.1.4","text":"CRAN release: 2023-02-10 user-facing changes. Patch release internal changes requested CRAN.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-213","dir":"Changelog","previous_headings":"","what":"readr 2.1.3","title":"readr 2.1.3","text":"CRAN release: 2022-10-01 Help files man/ re-generated, give rise valid HTML5. (impetus release, keep package safely CRAN.) mini-gapminder-africa.csv friends new example datasets accessible via readr_example(), added illustrate reading multiple files , single data frame.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-212","dir":"Changelog","previous_headings":"","what":"readr 2.1.2","title":"readr 2.1.2","text":"CRAN release: 2022-01-30 read_table(), read_log(), read_delim_chunked() (friends) gain show_col_types argument found elsewhere. read_*() functions now respect show_col_types argument option, even using first edition parsing engine (#1331). show_progress() uses rlang::is_interactive() instead base::interactive() (#1356). read_builtin() argument checking, catch obviously malformed input passing along utils::data() (#1361). chickens.csv whitespace-sample.txt new example datasets accessible via readr_example() (#1354).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-211","dir":"Changelog","previous_headings":"","what":"readr 2.1.1","title":"readr 2.1.1","text":"CRAN release: 2021-11-30 Jenny Bryan now maintainer. Fix buffer overflow trying parse integer field 64 characters long (#1326)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-210","dir":"Changelog","previous_headings":"","what":"readr 2.1.0","title":"readr 2.1.0","text":"CRAN release: 2021-11-11 readr functions read eagerly default. Unfortunately many users experienced frustration drawbacks lazy reading, particular locking files Windows, decided disable lazy reading default. However options(readr.read_lazy = TRUE) can used set default lazy desired. New readr.read_lazy global option control readr reads files lazily (#1266)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-202","dir":"Changelog","previous_headings":"","what":"readr 2.0.2","title":"readr 2.0.2","text":"CRAN release: 2021-09-27 minor test tweak compatibility testthat 3.1.0 (#@lionel-, #1304) write_rds() gains text= argument, control using text based object representation, like ascii= argument saveRDS() (#1270)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-201","dir":"Changelog","previous_headings":"","what":"readr 2.0.1","title":"readr 2.0.1","text":"CRAN release: 2021-08-10 options(readr.show_col_types = FALSE) now works intended (#1250) read_delim_chunked() now correctly respects chunk_size parameter (#1248) type_convert() gains guess_integer argument, passed guess_parser() (@jmbarbone, #1264) read_tsv() now correctly passes quote na arguments vroom::vroom() (#1254, #1255) Avoid spurious byte compilation errors due programmatically generated spec_*() functions.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-200","dir":"Changelog","previous_headings":"","what":"readr 2.0.0","title":"readr 2.0.0","text":"CRAN release: 2021-07-20","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"second-edition-changes-2-0-0","dir":"Changelog","previous_headings":"","what":"second edition changes","title":"readr 2.0.0","text":"readr 2.0.0 major release readr introduces new second edition parsing writing engine implemented via vroom package. engine takes advantage lazy reading, multi-threading performance characteristics modern SSD drives significantly improve performance reading writing compared first edition engine. continue support first edition number releases, eventually support first deprecated removed. can use with_edition() local_edition() functions temporarily change edition readr section code. e.g. with_edition(1, read_csv(\"my_file.csv\")) read my_file.csv first edition readr. readr::local_edition(1) placed top function script use first edition rest function script.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"lazy-reading-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Lazy reading","title":"readr 2.0.0","text":"Edition two uses lazy reading default. first call read_*() function delimiters newlines throughout entire file found, data actually read used program. can provide substantial speed improvements reading character data. particularly useful interactive exploration subset full dataset. However also means problematic values necessarily seen immediately, actually read. warning issued first time problem encountered, may happen initial reading. Run problems() dataset read entire dataset return problems found. Run problems(lazy = TRUE) want retrieve problems found far. Deleting files reading also impacted laziness. Windows open files deleted long process file open. readr keeps file open reading lazily means read, immediately delete file. readr cases close file completely read. However, know want able delete file reading best pass lazy = FALSE reading file.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"reading-multiple-files-at-once-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Reading multiple files at once","title":"readr 2.0.0","text":"Edition two built-support reading sets files columns one output table single command. Just pass filenames read vector reading function. First generate files read splitting nycflights dataset airline. can efficiently read one tibble passing filenames directly readr. filenames contain data, date sample collected, use id argument include paths column data. likely post-process paths keep relevant portion use case.","code":"library(nycflights13) purrr::iwalk( split(flights, flights$carrier), ~ { .x$carrier[[1]]; vroom::vroom_write(.x, glue::glue(\"flights_{.y}.tsv\"), delim = \"\\t\") } ) files <- fs::dir_ls(glob = \"flights*tsv\") files readr::read_tsv(files)"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"delimiter-guessing-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Delimiter guessing","title":"readr 2.0.0","text":"Edition two supports automatic guessing delimiters. can now use read_delim() without specifying delim argument many cases.","code":"x <- read_delim(readr_example(\"mtcars.csv\"))"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"literal-data-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Literal data","title":"readr 2.0.0","text":"edition one reading functions treated input newline vectors length > 1 literal data. edition two vectors length > 1 now assumed correspond multiple files. now explicit way represent literal data, putting () around input.","code":"readr::read_csv(I(\"a,b\\n1,2\"))"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"license-changes-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"License changes","title":"readr 2.0.0","text":"systematically re-licensing tidyverse r-lib packages use MIT license, make package licenses clear permissive possible. end readr vroom packages now released MIT license.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"deprecated-or-superseded-functions-and-features-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Deprecated or superseded functions and features","title":"readr 2.0.0","text":"melt_csv(), melt_delim(), melt_tsv() melt_fwf() superseded functions name meltr package. versions readr deprecated. functions rely first edition parsing code challenging update new parser. first edition parsing code eventually removed readr removed. read_table2() renamed read_table(), users expect read_table() work like utils::read.table(). want previous strict behavior read_table() can use read_fwf() fwf_empty() directly (#717). Normalizing newlines files just carriage returns \\r longer supported. last major OS use CR newline ‘classic’ Mac OS, final release 2001.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"other-second-edition-changes-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Other second edition changes","title":"readr 2.0.0","text":"read_*_chunked() functions now include specification attribute (#1143) read_*() functions gain col_select argument easily choose columns select. read_*() functions gain id argument optionally store file paths reading multiple files. read_*() functions gain name_repair argument control column names repaired. read_*() write_*() functions gain num_threads argument control number processing threads use (#1201) write_*() format_*() functions gain quote escape arguments, explicitly control fields quoted double quotes escaped. (#653, #759, #844, #993, #1018, #1083) write_*() functions gain progress argument display progress bar writing (#791). write_excel_csv() now defaults quote = \"\" (#759) write_tsv() now defaults quote = \"none\" (#993) read_table() now handles skipped lines unpaired quotes properly (#1180)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"additional-features-and-fixes-2-0-0","dir":"Changelog","previous_headings":"","what":"Additional features and fixes","title":"readr 2.0.0","text":"BH package longer dependency. boost C++ headers BH thousands files, can take long time extract compiling takes great deal memory, made readr difficult compile systems limited memory (#1147). readr now uses tzdb package parsing date-times (@DavisVaughan, r-lib/vroom#273) Chunked readers now support files INT_MAX (~ 2 Billion) number lines (#1177) Memory longer inadvertently leaks reading memory R connections (#1161) Invalid date formats longer can potentially crash R (#1151) col_factor() now throws informative error message given non-character levels (#1140) problems() now takes .Last.value default argument. lets run problems() without argument see problems previously read dataset. read_delim() fails sample parsing problems contains non-ASCII characters (@hidekoji, #1136) read_log() gains trim_ws argument (#738) read_rds() write_rds() gain refhook argument, pass functions handle references objects (#1206) read_rds() can now read .Rds files URLs (#1186) read_*() functions gain show_col_types argument, set FALSE turns showing column types unconditionally. type_convert() now throws warning input character columns (#1020) write_csv() now errors given matrix column (#1171) write_csv() now able write data duplicated column names (#1169) write_file() now forces argument opening output file (#1158)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-140","dir":"Changelog","previous_headings":"","what":"readr 1.4.0","title":"readr 1.4.0","text":"CRAN release: 2020-10-05","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"breaking-changes-1-4-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"readr 1.4.0","text":"write_*() functions first argument now file instead path, consistency read_*() functions. path deprecated removed future version readr (#1110, @brianrice2) write_*() functions now output NaN values way NA values, controlled na= argument. (#1082).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"new-features-1-4-0","dir":"Changelog","previous_headings":"","what":"New features","title":"readr 1.4.0","text":"now possible generate column specification tibble (data.frame) .col_spec() convert column specification short representation .character() cli package now used messages. runtime performance tables extreme number columns greatly improved (#825) Compressed files now detected magic numbers rather file extension (#1125) memory leak reading files now fixed (#1092) write_*() functions gain eol = argument control end line character used (#857). allows writing CSV files Windows newlines (CRLF) desired. Rcpp dependency removed favor cpp11. build system greatly simplified work systems.","code":"s <- as.col_spec(iris) s #> cols( #> Sepal.Length = col_double(), #> Sepal.Width = col_double(), #> Petal.Length = col_double(), #> Petal.Width = col_double(), #> Species = col_factor(levels = c(\"setosa\", \"versicolor\", \"virginica\"), ordered = FALSE, include_na = FALSE) #> ) as.character(s) #> [1] \"ddddf\""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"additional-features-and-fixes-1-4-0","dir":"Changelog","previous_headings":"","what":"Additional features and fixes","title":"readr 1.4.0","text":"full problem field now displayed problems tibble, intended (#444). New %h placeholder parsing unrestricted hours (<0 >23) support parsing durations (#549, @krlmlr). .character.col_spec() now handles logical columns well (#1127) fwf_positions(end) longer default argument must specified (#996) guess_parser() gains na argument removes NA values guessing (#1041). parse_guess() now passes na argument guess_parser() read_* functions now close properly connections, including errors like HTTP errors reading url (@cderv, #1050). read_delimited() longer mistakenly stats literal filenames (#1063) read_lines() now ignores quotations skipping lines (#991). read_lines(skip_empty_rows = TRUE) longer crashes file ends empty line (#968) write_*() functions now invisibly return input data frame unchanged, rather version factors dates converted strings. (@jesse-ross, #975). write_csv2() now formats decimal numbers consistently utils::write.csv2() (#1087) write_csv2() format_csv2() longer pad number columns whitespaces (@keesdeschepper, #1046). write_excel_csv() longer outputs byte order mark appending file (#1075). Uses tibble::data_frame updated tibble::tibble (tidyverse/dplyr#4069, @thays42, #1124, @brianrice2) read_delimited() now returns empty tibble::data_frame() rather signaling error given connection empty file (@pralitp, #963). helpful error trying write data frames list columns (@ellessenne, #938) type_convert() removes ‘spec’ attribute, current columns likely modified data types. ‘spec’ attribute set functions like read_delim() (@jimhester, @wibeasley, #1032). write_rds() now can specify Rds version use. default value 2 ’s compatible R versions prior 3.5.0 (@shrektan, #1001). Fixes issues related variable initialization C++ code (@michaelquinn32, ##1133).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-131","dir":"Changelog","previous_headings":"","what":"readr 1.3.1","title":"readr 1.3.1","text":"CRAN release: 2018-12-21 Column specifications now coloured printed. makes easy see glance column input different type rest. Colouring can disabled setting options(crayon.enabled = FALSE). .col_spec() can now use named character vectors, makes read_csv(\"file.csv\", col_types = c(xyz = \"c\")) equivalent read_csv(\"file.csv\", col_types = cols(xyz = col_character()) Fix skipping single quotes embedded double quoted strings, single quotes skipped commented lines (#944, #945). Fix compilation using custom architectures macOS (#919) Fix valgrind errors (#941)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-130","dir":"Changelog","previous_headings":"","what":"readr 1.3.0","title":"readr 1.3.0","text":"CRAN release: 2018-12-11","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"blank-line-skipping-1-3-0","dir":"Changelog","previous_headings":"Breaking Changes","what":"Blank line skipping","title":"readr 1.3.0","text":"readr’s blank line skipping modified consistent avoid edge cases affected behavior 1.2.0. skip parameter now behaves similar worked previous readr 1.2.0, addition parameter skip_blank_rows can used control fully blank lines skipped. (#923)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"tibble-data-frame-subclass-1-3-0","dir":"Changelog","previous_headings":"Breaking Changes","what":"tibble data frame subclass","title":"readr 1.3.0","text":"readr 1.3.0 returns results spec_tbl_df subclass. differs regular tibble spec attribute (holds column specification) lost soon object subset (normal tbl_df object returned). Historically tbl_df’s lost attributes subset. However recent versions tibble retain attributes subetting, spec_tbl_df subclass needed ensure previous behavior. break compatibility explicitly checking class returned object. way get backwards compatible behavior call subset arguments object, e.g. x[].","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"bugfixes-1-3-0","dir":"Changelog","previous_headings":"","what":"Bugfixes","title":"readr 1.3.0","text":"hms objects NA values now written without whitespace padding (#930). read_*() functions now return spec_tbl_df objects, differ regular tbl_df objects spec attribute removed (demoted regular tbl_df objects) soon subset (#934). write_csv2() now properly respects na argument (#928) Fixes compilation multiple architectures linux (#922). Fixes compilation R < 3.3.0","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-121","dir":"Changelog","previous_headings":"","what":"readr 1.2.1","title":"readr 1.2.1","text":"CRAN release: 2018-11-22 release skips clipboard tests CRAN servers","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-120","dir":"Changelog","previous_headings":"","what":"readr 1.2.0","title":"readr 1.2.0","text":"CRAN release: 2018-11-22","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"integer-column-guessing-1-2-0","dir":"Changelog","previous_headings":"Breaking Changes","what":"Integer column guessing","title":"readr 1.2.0","text":"readr functions longer guess columns type integer, instead columns guessed numeric. R uses 32 bit integers 64 bit doubles integers can stored doubles, guaranteeing loss information. change made remove errors numeric columns incorrectly guessed integers. know certain column integer like read can specifying column type explicitly col_types argument.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"blank-line-skipping-1-2-0","dir":"Changelog","previous_headings":"Breaking Changes","what":"Blank line skipping","title":"readr 1.2.0","text":"readr now always skips blank lines automatically parsing, may change number lines need pass skip parameter. instance file one blank line two lines want skip previously pass skip = 3, now need pass skip = 2.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"melt-functions-1-2-0","dir":"Changelog","previous_headings":"New features","what":"Melt functions","title":"readr 1.2.0","text":"now family melt_*() functions readr. functions store data ‘long’ ‘melted’ form, row corresponds single value dataset. form useful data ragged rectangular. Thanks Duncan Garmonsway (@nacnudus) great work idea implementation melt_*() functions!","code":"data <-\"a,b,c 1,2 w,x,y,z\" readr::melt_csv(data) #> # A tibble: 9 x 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 1 3 character c #> 4 2 1 integer 1 #> 5 2 2 integer 2 #> 6 3 1 character w #> 7 3 2 character x #> 8 3 3 character y #> 9 3 4 character z"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"connection-improvements-1-2-0","dir":"Changelog","previous_headings":"New features","what":"Connection improvements","title":"readr 1.2.0","text":"readr 1.2.0 changes R connections parsed readr. previous versions readr connections read -memory raw vector, passed readr functions. made reading connections small medium datasets fast, also meant dataset fit memory least twice (raw data, parsed data). also meant reading begin full vector read connection. Now instead write connection temporary file (R temporary directory), parse temporary file. means connections may take little longer read, also means longer need fit memory. also allows use chunked readers process data parts. Future improvements readr allow parse data connections streaming fashion, avoid many drawbacks either method.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"additional-new-features-1-2-0","dir":"Changelog","previous_headings":"New features","what":"Additional new features","title":"readr 1.2.0","text":"melt_*() functions added reading ragged data (#760, @nacnudus). AccumulateCallback R6 class added provide example accumulating values single result (#689, @blakeboswell). read_fwf() can now accept overlapping field specifications (#692, @gergness) type_convert() now allows character column specifications also silently skips non-character columns (#369, #699) parse_*() functions read_fwf() gain trim_ws argument control whether fields trimmed parsing (#636, #735). parse_number() now parses numbers scientific notation using e E (#684, @sambrady3). Add write_excel_csv2() function allow writing csv files comma decimal separator semicolon column separator (#753, @olgamie). read_*() files now support reading clipboard using clipboard() (#656). write_file() gains sep argument, specify line separator (#665). Allow files read via FTP SSH recognising sftp URL protocol (#707, @jdeboer). parse_date*() accepts%` local day week (#763, @tigertoes). Added function read_lines_raw_chunked() (#710, @gergness) write_csv2() added complement write_excel_csv2() allow writing csv file readable read_csv2() (#870, @cderv). .col_spec() now exported (#517). write*() functions gain quote_escape argument control quotes escaped output (#854). read*() functions now informative error trying read remote bz2 file (#891). spec_table2() function added correspond read_table2() (#778, @mawds). parse_factor() now levels = NULL default (#862, @mikmart). \"f\" can now used shortcode col_factor() cols() col_types argument read_delim() friends (#810, @mikmart). Functions now read connections temporary file rather -memory object (#610, #76).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"bug-fixes-1-2-0","dir":"Changelog","previous_headings":"","what":"Bug Fixes","title":"readr 1.2.0","text":"standardise_path() now uses case-insensitive comparison file extensions (#794). parse_guess() now guesses logical types given (lowercase) ‘true’ ‘false’ inputs (#818). read_*() now print progress bar running inside RStudio notebook chunk (#793) read_table2() now skips comments anywhere file (#908). parse_factor() now handles case empty strings separately, can factor level empty string (#864). read_delim() now correctly reads quoted headers embedded newlines (#784). fwf_positions() now always returns col_names character (#797). format_*() now explicitly marks ’s output encoding UTF-8 (#697). read_delim() now ignores whitespace delimiter quoted fields (#668). read_table2() now properly ignores blank lines end file like read_table() read_delim() (#657). read_delim(), read_table() read_table() now skip blank lines start file (#680, #747). guess_parser() now guesses logical type columns missing. useful binding multiple files together files missing columns. (#662). Column guessing now never guess integer type. avoids issues double columns incorrectly guessed integers integer values first 1000 (#645, #652). read_*() now converts string files UTF-8 parsing, convenient non-UTF-8 platforms cases (#730, @yutannihilation). write_csv() writes integers 10^15 without scientific notation (#765, @zeehio) read_*() longer throws “length NULL changed” warning trying resize skipped column (#750, #833). read_*() now handles non-ASCII paths properly R >=3.5.0 Windows (#838, @yutannihilation). read*()’s trim_ws parameter now trims spaces tabs (#767)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-111","dir":"Changelog","previous_headings":"","what":"readr 1.1.1","title":"readr 1.1.1","text":"CRAN release: 2017-05-16 Point release test compatibility tibble v1.3.1. Fixed undefined behavior localtime.c using locale(tz = \"\") loading timezone due incomplete reinitialization global locale.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-110","dir":"Changelog","previous_headings":"","what":"readr 1.1.0","title":"readr 1.1.0","text":"CRAN release: 2017-03-22","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"parser-improvements-1-1-0","dir":"Changelog","previous_headings":"New features","what":"Parser improvements","title":"readr 1.1.0","text":"parse_factor() gains include_na argument, include NA factor levels (#541). parse_factor() now can accept levels = NULL, allows one generate factor levels based data (like stringsAsFactors = TRUE) (#497). parse_numeric() now returns full string contains numbers (#548). parse_time() now correctly handles 12 /PM (#579). problems() now returns file path additional location error file (#581). read_csv2() gives message updates default locale (#443, @krlmlr). read_delim() now signals error given empty delimiter (#557). write_*() functions witting whole number doubles longer written trailing .0 (#526).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"whitespace--fixed-width-improvements-1-1-0","dir":"Changelog","previous_headings":"New features","what":"Whitespace / fixed width improvements","title":"readr 1.1.0","text":"fwf_cols() allows specifying col_positions argument read_fwf() named arguments either column positions widths (#616, @jrnold). fwf_empty() gains n argument control many lines read whitespace determine column structure (#518, @Yeedle). read_fwf() gives error message specifications overlapping columns (#534, @gergness) read_table() can now handle pipe() connections (#552). read_table() can now handle files many lines leading comments (#563). read_table2() allows number whitespace characters delimiters, exact replacement utils::read.table() (#608).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"writing-to-connections-1-1-0","dir":"Changelog","previous_headings":"","what":"Writing to connections","title":"readr 1.1.0","text":"write_*() functions now support writing binary connections. addition output filenames .gz, .bz2 .xz automatically open appropriate connection write compressed file. (#348) write_lines() now accepts list raw vectors (#542).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"miscellaneous-features-1-1-0","dir":"Changelog","previous_headings":"","what":"Miscellaneous features","title":"readr 1.1.0","text":"col_euro_double(), parse_euro_double(), col_numeric(), parse_numeric() removed. guess_encoding() returns tibble, works better lists raw vectors (returned read_lines_raw()). ListCallback R6 Class provide flexible return type callback functions (#568, @mmuurr) tibble::.tibble() now used construct tibbles (#538). read_csv, read_csv2, read_tsv gain quote argument, (#631, @noamross)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"bugfixes-1-1-0","dir":"Changelog","previous_headings":"","what":"Bugfixes","title":"readr 1.1.0","text":"parse_factor() now converts data UTF-8 based supplied locale (#615). read_*() functions guess_max argument now throw errors inappropriate inputs (#588). read_*_chunked() functions now properly end stream FALSE returned callback. read_delim() read_fwf() columns skipped using col_types now report correct column name (#573, @cb4ds). spec() declarations long now print properly (#597). read_table() print spec col_types NULL (#630, @jrnold). guess_encoding() now returns tibble ASCII input well (#641).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-100","dir":"Changelog","previous_headings":"","what":"readr 1.0.0","title":"readr 1.0.0","text":"CRAN release: 2016-08-03","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"column-guessing-1-0-0","dir":"Changelog","previous_headings":"","what":"Column guessing","title":"readr 1.0.0","text":"process readr guesses types columns received substantial overhaul make easier fix problems initial guesses aren’t correct, make easier generate reproducible code. Now column specifications printing default read file: can extract values fact spec(): makes easier quickly identify parsing problems fix (#314). column specification long, new cols_condense() used condense spec identifying common type setting default. particularly useful handful columns different type (#466). can also generating initial specification without parsing file using spec_csv(), spec_tsv(), etc. figured correct column types file, ’s often useful make parsing strict. can either copying pasting printed output, long specs, saving spec disk write_rds(). production scripts, combine stop_for_problems() (#465): input data changes form, ’ll fail fast error. can now also adjust number rows readr uses guess column types guess_max: can now access guessing algorithm R. guess_parser() tell parser readr select character vector (#377). ’ve made number fixes guessing algorithm: New example extdata/challenge.csv carefully created cause problems default column type guessing heuristics. Blank lines lines comments now skipped automatically without warning (#381, #321). Single ‘-’ ‘.’ now parsed characters, numbers (#297). Numbers followed single trailing character parsed character, numbers (#316). now guess times using time_format specified locale(). made number improvements reification col_types, col_names actual data: col_types long, subsetted correctly (#372, @jennybc). col_names short, added names numbered correctly (#374, @jennybc). Missing column name names now given default name (X2, X7 etc) (#318). Duplicated column names now deduplicated. changes generate warning; suppress supply explicit col_names (setting skip = 1 ’s existing ill-formed header). col_types() accepts named list input (#401).","code":"challenge <- read_csv(readr_example(\"challenge.csv\")) #> Parsed with column specification: #> cols( #> x = col_integer(), #> y = col_character() #> ) spec(challenge) #> cols( #> x = col_integer(), #> y = col_character() #> ) challenge <- read_csv(readr_example(\"challenge.csv\"), guess_max = 1500) #> Parsed with column specification: #> cols( #> x = col_double(), #> y = col_date(format = \"\") #> )"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"column-parsing-1-0-0","dir":"Changelog","previous_headings":"","what":"Column parsing","title":"readr 1.0.0","text":"date time parsers recognise three new format strings: %12 hour time format (#340). %AD %“automatic” date time parsers. slightly less flexible previous defaults. automatic date parser requires four digit year, accepts - / separators (#442). flexible time parser now requires colons hours minutes optional seconds (#424). %y %Y now strict require 2 4 characters respectively. Date time parsing functions received number small enhancements: parse_time() returns hms objects rather custom time class (#409). now correctly parses missing values (#398). parse_date() returns numeric vector (instead integer vector) (#357). parse_date(), parse_time() parse_datetime() gain na argument match parsers (#413). format argument omitted parse_date() parse_time(), date time formats specified locale used. now default %AD %respectively. can now parse partial dates parse_date() parse_datetime(), e.g. parse_date(\"2001\", \"%Y\") returns 2001-01-01. parse_number() slightly flexible - now parses numbers first ill-formed character. example parse_number(\"-3-\") parse_number(\"...3...\") now return -3 3 respectively. also fixed major bug parsing negative numbers yielded positive values (#308). parse_logical() now accepts 0, 1 well lowercase t, f, true, false.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"new-readers-and-writers-1-0-0","dir":"Changelog","previous_headings":"","what":"New readers and writers","title":"readr 1.0.0","text":"read_file_raw() reads complete file single raw vector (#451). read_*() functions gain quoted_na argument control whether missing values within quotes treated missing values strings (#295). write_excel_csv() can used write csv file UTF-8 BOM start, forces Excel read UTF-8 encoded (#375). write_lines() writes character vector file (#302). write_file() write single character raw vector file (#474). Experimental support chunked reading writing (read_*_chunked()) functions. API unstable subject change future (#427).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"minor-features-and-bug-fixes-1-0-0","dir":"Changelog","previous_headings":"","what":"Minor features and bug fixes","title":"readr 1.0.0","text":"Printing double values now uses implementation grisu3 algorithm speeds writing large numeric data frames ~10X. (#432) ‘.0’ appended whole number doubles, ensure read doubles well. (#483) readr imports tibble get consistent tbl_df behaviour (#317, #385). New example extdata/challenge.csv carefully created cause problems default column type guessing heuristics. default_locale() now sets default locale readr.default_locale rather regenerating call. (#416). locale() now automatically sets decimal mark set grouping mark. throws error accidentally set decimal grouping marks character (#450). read_*() can read long vectors, substantially increasing number rows can read (#309). read_*() functions return empty objects rather signaling error run empty file (#356, #441). read_delim() gains trim_ws argument (#312, noamross) read_fwf() received number improvements: read_fwf() now can now reliably read partial set columns (#322, #353, #469) fwf_widths() accepts negative column widths compatibility widths argument read.fwf() (#380, @leeper). can now read fixed width files ragged final columns, setting final end position fwf_positions() final width fwf_widths() NA (#353, @ghaarsma). fwf_empty() automatically. read_fwf() fwf_empty() can now skip commented lines setting comment argument (#334). read_lines() ignores embedded null’s strings (#338) gains na argument (#479). readr_example() makes easy access example files bundled readr. type_convert() now accepts NULL cols specification col_types (#369). write_delim() write_csv() now invisibly return input data frame (documented, #363). Doubles parsed boost::spirit::qi::long_double work around bug spirit library parsing large numbers (#412). Fix bug detecting column types single row files without headers (#333).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-022","dir":"Changelog","previous_headings":"","what":"readr 0.2.2","title":"readr 0.2.2","text":"CRAN release: 2015-10-22 Fix bug checking empty values missingness (caused valgrind issue random crashes).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-021","dir":"Changelog","previous_headings":"","what":"readr 0.2.1","title":"readr 0.2.1","text":"CRAN release: 2015-10-21 Fixes readr works Solaris.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-020","dir":"Changelog","previous_headings":"","what":"readr 0.2.0","title":"readr 0.2.0","text":"CRAN release: 2015-10-19","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"internationalisation-0-2-0","dir":"Changelog","previous_headings":"","what":"Internationalisation","title":"readr 0.2.0","text":"readr now strategy dealing settings vary place place: locales. default locale still US centric (R ), can now easily override default timezone, decimal separator, grouping mark, day & month names, date format, encoding. lead number changes: read_csv(), read_tsv(), read_fwf(), read_table(), read_lines(), read_file(), type_convert(), parse_vector() gain locale argument. locale() controls input settings vary place--place. col_euro_double() parse_euro_double() deprecated. Use decimal_mark parameter locale() instead. default encoding now UTF-8. load files UTF-8, set encoding parameter locale() (#40). New guess_encoding() function uses stringi help figure encoding file. parse_datetime() parse_date() %B %b use month names (full abbreviate) defined locale (#242). also inherit tz locale, rather using explicit tz parameter. See vignette(\"locales\") details.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"file-parsing-improvements-0-2-0","dir":"Changelog","previous_headings":"","what":"File parsing improvements","title":"readr 0.2.0","text":"cols() lets pick default column type columns otherwise explicitly named (#148). can refer parsers either full name (e.g. col_character()) one letter abbreviation (e.g. c). cols_only() allows load named columns. can also choose override default column type cols() (#72). read_fwf() now much careful new lines. line short, ’ll get warning instead silent mistake (#166, #254). Additionally, last column can now ragged: width last field silently extended hits next line break (#146). appears common feature “fixed” width files wild. read_csv(), read_tsv(), read_delim() etc: comment argument allows ignore comments (#68). trim_ws argument controls whether leading trailing whitespace removed. defaults TRUE (#137). Specifying wrong number column names, rows unexpected number columns, generates warning, rather error (#189). Multiple NA values can specified passing character vector na (#125). default changed na = c(\"\", \"NA\"). Specifying na = \"\" now works expected character columns (#114).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"column-parsing-improvements-0-2-0","dir":"Changelog","previous_headings":"","what":"Column parsing improvements","title":"readr 0.2.0","text":"Readr gains vignette(\"column-types\") describes defaults work override (#122). parse_character() gains better support embedded nulls: characters first null dropped warning (#202). parse_integer() parse_double() longer silently ignore trailing letters number (#221). New parse_time() col_time() allows parse times (hours, minutes, seconds) number seconds since midnight. format omitted, uses flexible parser looks hours, optional colon, minutes, optional colon, optional seconds, optional /pm (#249). parse_date() parse_datetime(): parse_datetime() longer incorrectly reads partial dates (e.g. 19, 1900, 1900-01) (#136). triggered common false positives re-reading ISO8601 spec, believe actually refer periods time, translated specific instant (#228). Compound formats “%D”, “%F”, “%R”, “%X”, “%T”, “%x” now parsed correctly, instead using ISO8601 parser (#178, @kmillar). “%.” now requires non-digit. New “%+” skips one non-digits. can now use %p refer /PM (/pm) (#126). %b %B formats (month abbreviated month name) ignore case matching (#219). Local (non-UTC) times without daylight savings now parsed correctly (#120, @andres-s). parse_number() somewhat flexible numeric parser designed read currencies percentages. reads first number string (using grouping mark defined locale). parse_numeric() deprecated name confusing - ’s flexible number parser, parser “numerics”, R collectively calls doubles integers. Use parse_number() instead. well improvements parser, ’ve also made number tweaks heuristics readr uses guess column types: New parse_guess() col_guess() explicitly guess column type. Bumped row inspection column typing guessing 100 1000. heuristics guessing col_integer() col_double() stricter. Numbers leading zeros now default parsed text, rather integers/doubles (#266). column guessed col_number() parses regular number ignoring grouping marks.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"minor-improvements-and-bug-fixes-0-2-0","dir":"Changelog","previous_headings":"","what":"Minor improvements and bug fixes","title":"readr 0.2.0","text":"Now use R’s platform independent iconv wrapper, thanks BDR (#149). Pathological zero row inputs (due empty input, skip n_max) now return zero row data frames (#119). guessing field types, ’s information go , use character instead logical (#124, #128). Concise col_types specification now understands ? (guess) - (skip) (#188). count_fields() starts counting 1, 0 (#200). format_csv() format_delim() make easy render csv delimited file string. fwf_empty() now works correctly col_names supplied (#186, #222). parse_*() gains na argument allows specify values converted missing. problems() now reports column names rather column numbers (#143). Whenever problem, first five problems printing warning message, can easily see ’s wrong. read_*() throws warning instead error col_types specifies non-existent column (#145, @alyst). read_*() can read remote gz compressed file (#163). read_delim() defaults escape_backslash = FALSE escape_double = TRUE consistency. n_max also affects number rows read guess column types (#224). read_lines() gains progress bar. now also correctly checks interrupts every 500,000 lines can interrupt long running jobs. also correctly estimates number lines file, considerably speeding reading large files (60s -> 15s 1.5 Gb file). read_lines_raw() allows read file list raw vectors, one element line. type_convert() gains NA trim_ws arguments, removes missing values determining column types. write_csv(), write_delim(), write_rds() invisibly return input can use pipe (#290). write_delim() generalises write_csv() write delimited format (#135). write_tsv() helpful wrapper tab separated files. Quotes used ’re needed (#116): string contains quote, delimiter, new line NA. Double vectors saved using amount precision .character() (#117). New na argument specifies missing values written (#187) POSIXt vectors saved ISO8601 compatible format (#134). longer fails silently can’t open target writing (#193, #172). write_rds() read_rds() wrap around readRDS() saveRDS(), defaulting compression (#140, @nicolasCoutin).","code":""}] +[{"path":[]},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement codeofconduct@posit.co. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://readr.tidyverse.org/dev/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired [Mozilla’s code conduct enforcement ladder][https://github.com/mozilla/inclusion]. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to readr","title":"Contributing to readr","text":"outlines propose change readr. detailed info contributing , tidyverse packages, please see development contributing guide.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"Contributing to readr","text":"can fix typos, spelling mistakes, grammatical errors documentation directly using GitHub web interface, long changes made source file. generally means ’ll need edit roxygen2 comments .R, .Rd file. can find .R file generates .Rd reading comment first line.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"bigger-changes","dir":"","previous_headings":"","what":"Bigger changes","title":"Contributing to readr","text":"want make bigger change, ’s good idea first file issue make sure someone team agrees ’s needed. ’ve found bug, please file issue illustrates bug minimal reprex (also help write unit test, needed).","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"Bigger changes","what":"Pull request process","title":"Contributing to readr","text":"Fork package clone onto computer. haven’t done , recommend using usethis::create_from_github(\"tidyverse/readr\", fork = TRUE). Install development dependencies devtools::install_dev_deps(), make sure package passes R CMD check running devtools::check(). R CMD check doesn’t pass cleanly, ’s good idea ask help continuing. Create Git branch pull request (PR). recommend using usethis::pr_init(\"brief-description--change\"). Make changes, commit git, create PR running usethis::pr_push(), following prompts browser. title PR briefly describe change. body PR contain Fixes #issue-number. user-facing changes, add bullet top NEWS.md (.e. just first header). Follow style described https://style.tidyverse.org/news.html.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"code-style","dir":"","previous_headings":"Bigger changes","what":"Code style","title":"Contributing to readr","text":"New code follow tidyverse style guide. can use styler package apply styles, please don’t restyle code nothing PR. use roxygen2, Markdown syntax, documentation. use testthat unit tests. Contributions test cases included easier accept.","code":""},{"path":"https://readr.tidyverse.org/dev/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contributing to readr","text":"Please note readr project released Contributor Code Conduct. contributing project agree abide terms.","code":""},{"path":"https://readr.tidyverse.org/dev/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2023 readr authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://readr.tidyverse.org/dev/MAINTENANCE.html","id":"current-state","dir":"","previous_headings":"","what":"Current state","title":"NA","text":"readr somewhat weird state currently. older v1 parsing code base, well calls vroom hood v2. addition still parts, like parse_() functions just use v1 code, currently analogous APIs vroom.","code":""},{"path":"https://readr.tidyverse.org/dev/MAINTENANCE.html","id":"known-outstanding-issues","dir":"","previous_headings":"","what":"Known outstanding issues","title":"NA","text":"Lazy reading causes problems people practice file locking windows. makes technique less effective otherwise unfortunately. v1 parser issues around skipping lines quoting. bunch flux skipped lines counted. known issues v2 parser see vroom MAINTENANCE.md document.","code":""},{"path":"https://readr.tidyverse.org/dev/MAINTENANCE.html","id":"future-directions","dir":"","previous_headings":"","what":"Future directions","title":"NA","text":"think eventually v1 parsing code removed entirely either vroom codebase included directly readr vroom archived, two continue exist readr functions lightweight shim calls vroom.","code":""},{"path":"https://readr.tidyverse.org/dev/SUPPORT.html","id":null,"dir":"","previous_headings":"","what":"Getting help with readr","title":"Getting help with readr","text":"Thanks using readr! filing issue, places explore pieces put together make process smooth possible.","code":""},{"path":"https://readr.tidyverse.org/dev/SUPPORT.html","id":"make-a-reprex","dir":"","previous_headings":"","what":"Make a reprex","title":"Getting help with readr","text":"Start making minimal reproducible example using reprex package. haven’t heard used reprex , ’re treat! Seriously, reprex make R-question-asking endeavors easier (pretty insane ROI five ten minutes ’ll take learn ’s ). additional reprex pointers, check Get help! section tidyverse site.","code":""},{"path":"https://readr.tidyverse.org/dev/SUPPORT.html","id":"where-to-ask","dir":"","previous_headings":"","what":"Where to ask?","title":"Getting help with readr","text":"Armed reprex, next step figure ask. ’s question: start community.rstudio.com, /StackOverflow. people answer questions. ’s bug: ’re right place, file issue. ’re sure: let community help figure ! problem bug feature request, can easily return report . opening new issue, sure search issues pull requests make sure bug hasn’t reported /already fixed development version. default, search pre-populated :issue :open. can edit qualifiers (e.g. :pr, :closed) needed. example, ’d simply remove :open search issues repo, open closed.","code":""},{"path":"https://readr.tidyverse.org/dev/SUPPORT.html","id":"what-happens-next","dir":"","previous_headings":"","what":"What happens next?","title":"Getting help with readr","text":"efficient possible, development tidyverse packages tends bursty, shouldn’t worry don’t get immediate response. Typically don’t look repo sufficient quantity issues accumulates, ’s burst intense activity focus efforts. makes development efficient avoids expensive context switching problems, cost taking longer get back . process makes good reprex particularly important might multiple months initial report start working . can’t reproduce bug, can’t fix !","code":""},{"path":"https://readr.tidyverse.org/dev/articles/column-types.html","id":"automatic-guessing","dir":"Articles","previous_headings":"","what":"Automatic guessing","title":"Column type","text":"don’t explicit specify column types col_types argument, readr attempt guess using simple heuristics. default, inspect 1000 values, evenly spaced first last row. heuristic designed always fast (matter large file ) , experience, good job cases. needed, can request readr use rows supplying guess_max argument. can even supply guess_max = Inf use every row guess column types. might wonder isn’t default. ’s ’s slow: look every column twice, determine type parse value. cases, ’re best supplying col_types .","code":""},{"path":"https://readr.tidyverse.org/dev/articles/column-types.html","id":"legacy-behavior","dir":"Articles","previous_headings":"Automatic guessing","what":"Legacy behavior","title":"Column type","text":"Column type guessing substantially worse first edition readr (meaning, prior v2.0.0), always looked first 1000 rows, application Murphy’s Law, appears many real csv files lots empty values start, followed “excitement” later file. Let’s demonstrate problem slightly tricky file: column x mostly empty, numeric data end, row 1001. first edition parser doesn’t guess right type x 2 becomes NA: specific case, can fix problem marginally increasing guess_max: Unlike second edition, don’t recommend using guess_max = Inf legacy parser, engine pre-allocates large amount memory face uncertainty. means reading guess_max = Inf can extremely slow might even crash R session. Instead specify col_types:","code":"tricky_dat <- tibble::tibble( x = rep(c(\"\", \"2\"), c(1000, 1)), y = \"y\" ) tfile <- tempfile(\"tricky-column-type-guessing-\", fileext = \".csv\") write_csv(tricky_dat, tfile) df <- with_edition(1, read_csv(tfile)) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> x = col_logical(), #> y = col_character() #> ) #> Warning: 1 parsing failure. #> row col expected actual file #> 1001 x 1/0/T/F/TRUE/FALSE 2 '/tmp/RtmpZir3ez/tricky-column-type-guessing-2378666c52dc.csv' tail(df) #> # A tibble: 6 × 2 #> x y #> #> 1 NA y #> 2 NA y #> 3 NA y #> 4 NA y #> 5 NA y #> 6 NA y df <- with_edition(1, read_csv(tfile, guess_max = 1001)) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> x = col_double(), #> y = col_character() #> ) tail(df) #> # A tibble: 6 × 2 #> x y #> #> 1 NA y #> 2 NA y #> 3 NA y #> 4 NA y #> 5 NA y #> 6 2 y df <- with_edition(1, read_csv(tfile, col_types = list(x = col_double()))) tail(df) #> # A tibble: 6 × 2 #> x y #> #> 1 NA y #> 2 NA y #> 3 NA y #> 4 NA y #> 5 NA y #> 6 2 y"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"names-of-months-and-days","dir":"Articles","previous_headings":"Dates and times","what":"Names of months and days","title":"Locales","text":"first argument locale() date_names, controls values used month day names. easiest way specify ISO 639 language code: don’t already know code language, Wikipedia good list. Currently readr 185 languages available. can list date_names_langs(). Specifying locale allows parse dates languages: many languages, ’s common find diacritics stripped can stored ASCII. can tell locale asciify option: Note quality translations variable, especially rarer languages. discover ’re quite right data, can create date_names(). following example creates locale Māori date names:","code":"locale(\"ko\") # Korean #> #> Numbers: 123,456.78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: 일요일 (일), 월요일 (월), 화요일 (화), 수요일 (수), 목요일 (목), #> 금요일 (금), 토요일 (토) #> Months: 1월, 2월, 3월, 4월, 5월, 6월, 7월, 8월, 9월, 10월, 11월, 12월 #> AM/PM: 오전/오후 locale(\"fr\") # French #> #> Numbers: 123,456.78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: dimanche (dim.), lundi (lun.), mardi (mar.), mercredi (mer.), #> jeudi (jeu.), vendredi (ven.), samedi (sam.) #> Months: janvier (janv.), février (févr.), mars (mars), avril (avr.), mai #> (mai), juin (juin), juillet (juil.), août (août), #> septembre (sept.), octobre (oct.), novembre (nov.), #> décembre (déc.) #> AM/PM: AM/PM parse_date(\"1 janvier 2015\", \"%d %B %Y\", locale = locale(\"fr\")) #> [1] \"2015-01-01\" parse_date(\"14 oct. 1979\", \"%d %b %Y\", locale = locale(\"fr\")) #> [1] \"1979-10-14\" parse_date(\"1 août 2015\", \"%d %B %Y\", locale = locale(\"fr\")) #> [1] \"2015-08-01\" parse_date(\"1 aout 2015\", \"%d %B %Y\", locale = locale(\"fr\", asciify = TRUE)) #> [1] \"2015-08-01\" maori <- locale(date_names( day = c(\"Rātapu\", \"Rāhina\", \"Rātū\", \"Rāapa\", \"Rāpare\", \"Rāmere\", \"Rāhoroi\"), mon = c(\"Kohi-tātea\", \"Hui-tanguru\", \"Poutū-te-rangi\", \"Paenga-whāwhā\", \"Haratua\", \"Pipiri\", \"Hōngongoi\", \"Here-turi-kōkā\", \"Mahuru\", \"Whiringa-ā-nuku\", \"Whiringa-ā-rangi\", \"Hakihea\") ))"},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"timezones","dir":"Articles","previous_headings":"Dates and times","what":"Timezones","title":"Locales","text":"Unless otherwise specified, readr assumes times UTC, Universal Coordinated Time (successor GMT almost intents identical). UTC suitable data doesn’t daylight savings - avoids whole class potential problems. data isn’t already UTC, ’ll need supply tz locale: can see complete list time zones OlsonNames(). ’re American, note “EST” Canadian time zone DST. ’s Eastern Standard Time! Instead use: PST/PDT = “US/Pacific” CST/CDT = “US/Central” MST/MDT = “US/Mountain” EST/EDT = “US/Eastern” (Note specific time zones smaller areas don’t follow rules. example, “US/Arizona”, follows mostly follows mountain time, doesn’t daylight savings. ’re dealing historical data, might need even specific zone like “America/North_Dakota/New_Salem” - get accurate time zones.) Note used defaults. individual times timezones ’re using “%Z” (name, e.g. “America/Chicago”) “%z” (offset UTC, e.g. “+0800”), ’ll override defaults. ’s currently good way parse times use US abbreviations. Note date R, changing time zone just changes printed representation - still represents instants time. ’ve loaded non-UTC data, want display UTC, try snippet code:","code":"parse_datetime(\"2001-10-10 20:10\") #> [1] \"2001-10-10 20:10:00 UTC\" parse_datetime(\"2001-10-10 20:10\", locale = locale(tz = \"Pacific/Auckland\")) #> [1] \"2001-10-10 20:10:00 NZDT\" parse_datetime(\"2001-10-10 20:10\", locale = locale(tz = \"Europe/Dublin\")) #> [1] \"2001-10-10 20:10:00 IST\" is_datetime <- sapply(df, inherits, \"POSIXct\") df[is_datetime] <- lapply(df[is_datetime], function(x) { attr(x, \"tzone\") <- \"UTC\" x })"},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"default-formats","dir":"Articles","previous_headings":"Dates and times","what":"Default formats","title":"Locales","text":"Locales also provide default date time formats. date format used guessing column types. default date format %AD, flexible YMD parser (see ?parse_date): ’re American, might want use illogical date system:: time format also used guessing column types. default time format %, flexible HMS parser (see ?parse_time):","code":"str(parse_guess(\"2010-10-10\")) #> Date[1:1], format: \"2010-10-10\" str(parse_guess(\"2010/10/10\")) #> Date[1:1], format: \"2010-10-10\" str(parse_guess(\"01/31/2013\")) #> chr \"01/31/2013\" str(parse_guess(\"01/31/2013\", locale = locale(date_format = \"%m/%d/%Y\"))) #> Date[1:1], format: \"2013-01-31\" str(parse_guess(\"17:55:14\")) #> 'hms' num 17:55:14 #> - attr(*, \"units\")= chr \"secs\" str(parse_guess(\"5:55:14 PM\")) #> 'hms' num 17:55:14 #> - attr(*, \"units\")= chr \"secs\" # Example of a non-standard time str(parse_guess(\"h5m55s14 PM\")) #> chr \"h5m55s14 PM\" str(parse_guess(\"h5m55s14 PM\", locale = locale(time_format = \"h%Hm%Ms%S %p\"))) #> 'hms' num 17:55:14 #> - attr(*, \"units\")= chr \"secs\""},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"character","dir":"Articles","previous_headings":"","what":"Character","title":"Locales","text":"readr functions yield strings encoded UTF-8. encoding likely give good results widest variety settings. default, readr assumes input also UTF-8. less likely case, especially ’re working older datasets. following code illustrates problems encodings: don’t know encoding file uses, try guess_encoding(). ’s 100% perfect (’s fundamentally heuristic), least get pointed right direction:","code":"library(stringi) x <- \"Émigré cause célèbre déjà vu.\\n\" y <- stri_conv(x, \"UTF-8\", \"latin1\") # These strings look like they're identical: x #> [1] \"Émigré cause célèbre déjà vu.\\n\" y #> [1] \"Émigré cause célèbre déjà vu.\\n\" identical(x, y) #> [1] TRUE # But they have different encodings: Encoding(x) #> [1] \"UTF-8\" Encoding(y) #> [1] \"latin1\" # That means while they print the same, their raw (binary) # representation is actually quite different: charToRaw(x) #> [1] c3 89 6d 69 67 72 c3 a9 20 63 61 75 73 65 20 63 c3 a9 6c c3 a8 62 72 #> [24] 65 20 64 c3 a9 6a c3 a0 20 76 75 2e 0a charToRaw(y) #> [1] c9 6d 69 67 72 e9 20 63 61 75 73 65 20 63 e9 6c e8 62 72 65 20 64 e9 #> [24] 6a e0 20 76 75 2e 0a # readr expects strings to be encoded as UTF-8. If they're # not, you'll get weird characters parse_character(x) #> [1] \"Émigré cause célèbre déjà vu.\\n\" parse_character(y) #> [1] \"\\xc9migr\\xe9 cause c\\xe9l\\xe8bre d\\xe9j\\xe0 vu.\\n\" # If you know the encoding, supply it: parse_character(y, locale = locale(encoding = \"latin1\")) #> [1] \"Émigré cause célèbre déjà vu.\\n\" guess_encoding(x) #> # A tibble: 3 × 2 #> encoding confidence #> #> 1 UTF-8 1 #> 2 windows-1250 0.34 #> 3 windows-1252 0.26 guess_encoding(y) #> # A tibble: 2 × 2 #> encoding confidence #> #> 1 ISO-8859-2 0.4 #> 2 ISO-8859-1 0.3 # Note that the first guess produces a valid string, but isn't correct: parse_character(y, locale = locale(encoding = \"ISO-8859-2\")) #> [1] \"Émigré cause célčbre déjŕ vu.\\n\" # But ISO-8859-1 is another name for latin1 parse_character(y, locale = locale(encoding = \"ISO-8859-1\")) #> [1] \"Émigré cause célèbre déjà vu.\\n\""},{"path":"https://readr.tidyverse.org/dev/articles/locales.html","id":"numbers","dir":"Articles","previous_headings":"","what":"Numbers","title":"Locales","text":"countries use decimal point, others use decimal comma. decimal_mark option controls readr uses parsing doubles: Additionally, writing big numbers, might 1,000,000, 1.000.000, 1 000 000, 1'000'000. grouping mark ignored flexible number parser:","code":"parse_double(\"1,23\", locale = locale(decimal_mark = \",\")) #> [1] 1.23 parse_number(\"$1,234.56\") #> [1] 1234.56 parse_number(\"$1.234,56\", locale = locale(decimal_mark = \",\", grouping_mark = \".\") ) #> [1] 1234.56 # readr is smart enough to guess that if you're using , for decimals then # you're probably using . for grouping: parse_number(\"$1.234,56\", locale = locale(decimal_mark = \",\")) #> [1] 1234.56"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"vector-parsers","dir":"Articles","previous_headings":"","what":"Vector parsers","title":"Introduction to readr","text":"’s easiest learn vector parses using parse_ functions. take character vector options. return new vector length old, along attribute describing problems.","code":""},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"atomic-vectors","dir":"Articles","previous_headings":"Vector parsers","what":"Atomic vectors","title":"Introduction to readr","text":"parse_logical(), parse_integer(), parse_double(), parse_character() straightforward parsers produce corresponding atomic vector. default, readr expects . decimal mark , grouping mark. can override default using locale(), described vignette(\"locales\").","code":"parse_integer(c(\"1\", \"2\", \"3\")) #> [1] 1 2 3 parse_double(c(\"1.56\", \"2.34\", \"3.56\")) #> [1] 1.56 2.34 3.56 parse_logical(c(\"true\", \"false\")) #> [1] TRUE FALSE"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"flexible-numeric-parser","dir":"Articles","previous_headings":"Vector parsers","what":"Flexible numeric parser","title":"Introduction to readr","text":"parse_integer() parse_double() strict: input string must single number leading trailing characters. parse_number() flexible: ignores non-numeric prefixes suffixes, knows deal grouping marks. makes suitable reading currencies percentages:","code":"parse_number(c(\"0%\", \"10%\", \"150%\")) #> [1] 0 10 150 parse_number(c(\"$1,234.5\", \"$12.45\")) #> [1] 1234.50 12.45"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"datetimes","dir":"Articles","previous_headings":"Vector parsers","what":"Date/times","title":"Introduction to readr","text":"readr supports three types date/time data: dates: number days since 1970-01-01. times: number seconds since midnight. datetimes: number seconds since midnight 1970-01-01. function takes format argument describes format string. specified, uses default value: parse_datetime() recognises ISO8601 datetimes. parse_date() uses date_format specified locale(). default value %AD uses automatic date parser recognises dates format Y-m-d Y/m/d. parse_time() uses time_format specified locale(). default value %uses automatic time parser recognises times form H:M optionally followed seconds /pm. cases, need supply format, documented parse_datetime():","code":"parse_datetime(\"2010-10-01 21:45\") #> [1] \"2010-10-01 21:45:00 UTC\" parse_date(\"2010-10-01\") #> [1] \"2010-10-01\" parse_time(\"1:00pm\") #> 13:00:00 parse_datetime(\"1 January, 2010\", \"%d %B, %Y\") #> [1] \"2010-01-01 UTC\" parse_datetime(\"02/02/15\", \"%m/%d/%y\") #> [1] \"2015-02-02 UTC\""},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"factors","dir":"Articles","previous_headings":"Vector parsers","what":"Factors","title":"Introduction to readr","text":"reading column known set values, can read directly factor. parse_factor() generate warning value supplied levels.","code":"parse_factor(c(\"a\", \"b\", \"a\"), levels = c(\"a\", \"b\", \"c\")) #> [1] a b a #> Levels: a b c parse_factor(c(\"a\", \"b\", \"d\"), levels = c(\"a\", \"b\", \"c\")) #> Warning: 1 parsing failure. #> row col expected actual #> 3 -- value in level set d #> [1] a b #> attr(,\"problems\") #> # A tibble: 1 × 4 #> row col expected actual #> #> 1 3 NA value in level set d #> Levels: a b c"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"column-specification","dir":"Articles","previous_headings":"","what":"Column specification","title":"Introduction to readr","text":"tedious specify type every column reading file. Instead readr, uses heuristics guess type column. can access results using guess_parser(): guessing policies described documentation individual functions. Guesses fairly strict. example, don’t guess currencies numbers, even though can parse : two parsers never guessed: col_skip() col_factor(). always need supply explicitly. can see specification readr generate column file using spec_csv(), spec_tsv() : bigger files, can often make specification simpler changing default column type using cols_condense() default readr looks first 1000 rows. keeps file parsing speedy, can generate incorrect guesses. example, challenge.csv column types change row 1001, readr guesses wrong types. One way resolve problem increase number rows: Another way manually specify col_type, described .","code":"guess_parser(c(\"a\", \"b\", \"c\")) #> [1] \"character\" guess_parser(c(\"1\", \"2\", \"3\")) #> [1] \"double\" guess_parser(c(\"1,000\", \"2,000\", \"3,000\")) #> [1] \"number\" guess_parser(c(\"2001/10/10\")) #> [1] \"date\" guess_parser(\"$1,234\") #> [1] \"character\" parse_number(\"$1,234\") #> [1] 1234 x <- spec_csv(readr_example(\"challenge.csv\")) mtcars_spec <- spec_csv(readr_example(\"mtcars.csv\")) mtcars_spec #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) cols_condense(mtcars_spec) #> cols( #> .default = col_double() #> ) x <- spec_csv(readr_example(\"challenge.csv\"), guess_max = 1001)"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"rectangular-parsers","dir":"Articles","previous_headings":"","what":"Rectangular parsers","title":"Introduction to readr","text":"readr comes five parsers rectangular file formats: read_csv() read_csv2() csv files read_tsv() tabs separated files read_fwf() fixed-width files read_log() web log files functions firsts calls spec_xxx() (described ), parses file according column specification: rectangular parsing functions almost always succeed; ’ll fail format severely messed . Instead, readr generate data frame problems. first printed , can access problems(): ’ve already seen one way handling bad guesses: increasing number rows used guess type column. Another approach manually supply column specification.","code":"df1 <- read_csv(readr_example(\"challenge.csv\")) #> Rows: 2000 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): x #> date (1): y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. problems(df1) #> # A tibble: 0 × 5 #> # ℹ 5 variables: row , col , expected , actual , #> # file df2 <- read_csv(readr_example(\"challenge.csv\"), guess_max = 1001) #> Rows: 2000 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): x #> date (1): y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message."},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"overriding-the-defaults","dir":"Articles","previous_headings":"Rectangular parsers","what":"Overriding the defaults","title":"Introduction to readr","text":"previous examples, may noticed readr printed column specification used parse file: can also access fact using spec(): (also allows access full column specification ’re reading wide file. default, readr print specification first 20 columns.) want manually specify column types, can start copying pasting code, tweaking fix parsing problems. general, ’s good practice supply explicit column specification. work, ensures get warnings data changes unexpected ways. really strict, can use stop_for_problems(df3). throw error parsing problems, forcing fix problems proceeding analysis.","code":"#> Parsed with column specification: #> cols( #> x = col_integer(), #> y = col_character() #> ) spec(df1) #> cols( #> x = col_double(), #> y = col_date(format = \"\") #> ) spec(df2) #> cols( #> x = col_double(), #> y = col_date(format = \"\") #> ) df3 <- read_csv( readr_example(\"challenge.csv\"), col_types = list( x = col_double(), y = col_date(format = \"\") ) )"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"available-column-specifications","dir":"Articles","previous_headings":"Rectangular parsers","what":"Available column specifications","title":"Introduction to readr","text":"available specifications : (string abbreviations brackets) col_logical() [l], containing T, F, TRUE FALSE. col_integer() [], integers. col_double() [d], doubles. col_character() [c], everything else. col_factor(levels, ordered) [f], fixed set values. col_date(format = \"\") [D]: locale’s date_format. col_time(format = \"\") [t]: locale’s time_format. col_datetime(format = \"\") [T]: ISO8601 date times col_number() [n], numbers containing grouping_mark col_skip() [_, -], don’t import column. col_guess() [?], parse using “best” type based input. Use col_types argument override default choices. two ways use : string: \"dc__d\": read first column double, second character, skip next two read last column double. (’s way use form types take additional parameters.) (named) list col objects: , abbreviations: omitted columns parsed automatically, previous call lead result : can also set default type used instead relying automatic detection columns don’t specify: want read specified columns, use cols_only():","code":"read_csv(\"iris.csv\", col_types = list( Sepal.Length = col_double(), Sepal.Width = col_double(), Petal.Length = col_double(), Petal.Width = col_double(), Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\")) )) read_csv(\"iris.csv\", col_types = list( Sepal.Length = \"d\", Sepal.Width = \"d\", Petal.Length = \"d\", Petal.Width = \"d\", Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\")) )) read_csv(\"iris.csv\", col_types = list( Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\"))) ) read_csv(\"iris.csv\", col_types = list( Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\")), .default = col_double()) ) read_csv(\"iris.csv\", col_types = cols_only( Species = col_factor(c(\"setosa\", \"versicolor\", \"virginica\"))) )"},{"path":"https://readr.tidyverse.org/dev/articles/readr.html","id":"output","dir":"Articles","previous_headings":"Rectangular parsers","what":"Output","title":"Introduction to readr","text":"output functions tibble. Note characters never automatically converted factors (.e. stringsAsFactors = FALSE) column names left , munged valid R identifiers (.e. check.names = TRUE). Row names never set. Attributes store column specification (spec()) parsing problems (problems()).","code":""},{"path":"https://readr.tidyverse.org/dev/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Hadley Wickham. Author. Jim Hester. Author. Romain Francois. Contributor. Jennifer Bryan. Author, maintainer. Shelby Bearrows. Contributor. . Copyright holder, funder. https://github.com/mandreyel/. Copyright holder. mio library Jukka Jylänki. Contributor, copyright holder. grisu3 implementation Mikkel Jørgensen. Contributor, copyright holder. grisu3 implementation","code":""},{"path":"https://readr.tidyverse.org/dev/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Wickham H, Hester J, Bryan J (2024). readr: Read Rectangular Text Data. R package version 2.1.4.9000, https://github.com/tidyverse/readr, https://readr.tidyverse.org.","code":"@Manual{, title = {readr: Read Rectangular Text Data}, author = {Hadley Wickham and Jim Hester and Jennifer Bryan}, year = {2024}, note = {R package version 2.1.4.9000, https://github.com/tidyverse/readr}, url = {https://readr.tidyverse.org}, }"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Read Rectangular Text Data","text":"goal readr provide fast friendly way read rectangular data delimited files, comma-separated values (CSV) tab-separated values (TSV). designed parse many types data found wild, providing informative problem report parsing leads unexpected results. new readr, best place start data import chapter R Data Science.","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Read Rectangular Text Data","text":"","code":"# The easiest way to get readr is to install the whole tidyverse: install.packages(\"tidyverse\") # Alternatively, install just readr: install.packages(\"readr\") # Or you can install the development version from GitHub: # install.packages(\"pak\") pak::pak(\"tidyverse/readr\")"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Read Rectangular Text Data","text":"readr part core tidyverse, can load : course, can also load readr individual package: read rectangular dataset readr, combine two pieces: function parses lines file individual fields column specification. readr supports following file formats read_*() functions: read_csv(): comma-separated values (CSV) read_tsv(): tab-separated values (TSV) read_csv2(): semicolon-separated values , decimal mark read_delim(): delimited files (CSV TSV important special cases) read_fwf(): fixed-width files read_table(): whitespace-separated files read_log(): web log files column specification describes column converted character vector specific data type (e.g. character, numeric, datetime, etc.). absence column specification, readr guess column types data. vignette(\"column-types\") gives detail readr guesses column types. Column type guessing handy, especially data exploration, ’s important remember just guesses. data analysis project matures past exploratory phase, best strategy provide explicit column types. following example loads sample file bundled readr guesses column types: Note readr prints column types – guessed column types, case. useful allows check columns read expect. haven’t, means need provide column specification. sounds like lot trouble, luckily readr affords nice workflow . Use spec() retrieve (guessed) column specification initial effort. Now can copy, paste, tweak , create explicit readr call expresses desired column types. express sex factor levels rooster hen, order, eggs_laid integer. vignette(\"readr\") gives expanded introduction readr.","code":"library(tidyverse) #> ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── #> ✔ dplyr 1.1.4 ✔ readr 2.1.4.9000 #> ✔ forcats 1.0.0 ✔ stringr 1.5.1 #> ✔ ggplot2 3.4.3 ✔ tibble 3.2.1 #> ✔ lubridate 1.9.3 ✔ tidyr 1.3.0 #> ✔ purrr 1.0.2 #> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── #> ✖ dplyr::filter() masks stats::filter() #> ✖ dplyr::lag() masks stats::lag() #> ℹ Use the conflicted package () to force all conflicts to become errors library(readr) (chickens <- read_csv(readr_example(\"chickens.csv\"))) #> Rows: 5 Columns: 4 #> ── Column specification ──────────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (3): chicken, sex, motto #> dbl (1): eggs_laid #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 4 #> chicken sex eggs_laid motto #> #> 1 Foghorn Leghorn rooster 0 That's a joke, ah say, that's a jok… #> 2 Chicken Little hen 3 The sky is falling! #> 3 Ginger hen 12 Listen. We'll either die free chick… #> 4 Camilla the Chicken hen 7 Bawk, buck, ba-gawk. #> 5 Ernie The Giant Chicken rooster 0 Put Captain Solo in the cargo hold. spec(chickens) #> cols( #> chicken = col_character(), #> sex = col_character(), #> eggs_laid = col_double(), #> motto = col_character() #> ) chickens <- read_csv( readr_example(\"chickens.csv\"), col_types = cols( chicken = col_character(), sex = col_factor(levels = c(\"rooster\", \"hen\")), eggs_laid = col_integer(), motto = col_character() ) ) chickens #> # A tibble: 5 × 4 #> chicken sex eggs_laid motto #> #> 1 Foghorn Leghorn rooster 0 That's a joke, ah say, that's a jok… #> 2 Chicken Little hen 3 The sky is falling! #> 3 Ginger hen 12 Listen. We'll either die free chick… #> 4 Camilla the Chicken hen 7 Bawk, buck, ba-gawk. #> 5 Ernie The Giant Chicken rooster 0 Put Captain Solo in the cargo hold."},{"path":"https://readr.tidyverse.org/dev/index.html","id":"editions","dir":"","previous_headings":"","what":"Editions","title":"Read Rectangular Text Data","text":"readr got new parsing engine version 2.0.0 (released July 2021). -called second edition, readr calls vroom::vroom(), default. parsing engine readr versions prior 2.0.0 now called first edition. ’re using readr >= 2.0.0, can still access first edition parsing via functions with_edition(1, ...) local_edition(1). , obviously, ’re using readr < 2.0.0, get first edition parsing, definition, ’s . continue support first edition number releases, overall goal make second edition uniformly better first. Therefore plan eventually deprecate remove first edition code. New code actively-maintained code use second edition. workarounds with_edition(1, ...) local_edition(1) offered pragmatic way patch legacy code temporary solution infelicities identified second edition matures.","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"alternatives","dir":"","previous_headings":"","what":"Alternatives","title":"Read Rectangular Text Data","text":"two main alternatives readr: base R data.table’s fread(). important differences discussed .","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"base-r","dir":"","previous_headings":"Alternatives","what":"Base R","title":"Read Rectangular Text Data","text":"Compared corresponding base functions, readr functions: Use consistent naming scheme parameters (e.g. col_names col_types header colClasses). generally much faster (10x-100x) depending dataset. Leave strings default, automatically parse common date/time formats. helpful progress bar loading going take . functions work exactly way regardless current locale. override US-centric defaults, use locale().","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"datatable-and-fread","dir":"","previous_headings":"Alternatives","what":"data.table and fread()","title":"Read Rectangular Text Data","text":"data.table function similar read_csv() called fread(). Compared fread(), readr functions: sometimes slower, particularly numeric heavy data. Can automatically guess parameters, basically encourage explicit specification , e.g., delimiter, skipped rows, header row. Follow tidyverse-wide conventions, returning tibble, standard approach column name repair, common mini-language column selection.","code":""},{"path":"https://readr.tidyverse.org/dev/index.html","id":"acknowledgements","dir":"","previous_headings":"","what":"Acknowledgements","title":"Read Rectangular Text Data","text":"Thanks : Joe Cheng showing beauty deterministic finite automata parsing, teaching write tokenizer. JJ Allaire helping come design makes copies, easy extend. Dirk Eddelbuettel coming name!","code":""},{"path":"https://readr.tidyverse.org/dev/reference/Tokenizers.html","id":null,"dir":"Reference","previous_headings":"","what":"Tokenizers. — Tokenizers","title":"Tokenizers. — Tokenizers","text":"Explicitly create tokenizer objects. Usually call function, instead use one use friendly wrappers like read_csv().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/Tokenizers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tokenizers. — Tokenizers","text":"","code":"tokenizer_delim( delim, quote = \"\\\"\", na = \"NA\", quoted_na = TRUE, comment = \"\", trim_ws = TRUE, escape_double = TRUE, escape_backslash = FALSE, skip_empty_rows = TRUE ) tokenizer_csv( na = \"NA\", quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip_empty_rows = TRUE ) tokenizer_tsv( na = \"NA\", quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip_empty_rows = TRUE ) tokenizer_line(na = character(), skip_empty_rows = TRUE) tokenizer_log(trim_ws) tokenizer_fwf( begin, end, na = \"NA\", comment = \"\", trim_ws = TRUE, skip_empty_rows = TRUE ) tokenizer_ws(na = \"NA\", comment = \"\", skip_empty_rows = TRUE)"},{"path":"https://readr.tidyverse.org/dev/reference/Tokenizers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tokenizers. — Tokenizers","text":"delim Single character used separate fields within record. quote Single character used quote strings. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. begin, end Begin end offsets file. C++ offsets first column column zero, ranges [begin, end) (.e inclusive-exclusive).","code":""},{"path":"https://readr.tidyverse.org/dev/reference/Tokenizers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tokenizers. — Tokenizers","text":"","code":"tokenizer_csv() #> $delim #> [1] \",\" #> #> $quote #> [1] \"\\\"\" #> #> $na #> [1] \"NA\" #> #> $quoted_na #> [1] TRUE #> #> $comment #> [1] \"\" #> #> $trim_ws #> [1] TRUE #> #> $escape_double #> [1] TRUE #> #> $escape_backslash #> [1] FALSE #> #> $skip_empty_rows #> [1] TRUE #> #> attr(,\"class\") #> [1] \"tokenizer_delim\""},{"path":"https://readr.tidyverse.org/dev/reference/as.col_spec.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a column specification — as.col_spec","title":"Generate a column specification — as.col_spec","text":"useful generating specification using short form","code":""},{"path":"https://readr.tidyverse.org/dev/reference/as.col_spec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a column specification — as.col_spec","text":"","code":"as.col_spec(x)"},{"path":"https://readr.tidyverse.org/dev/reference/as.col_spec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a column specification — as.col_spec","text":"x Input object","code":""},{"path":"https://readr.tidyverse.org/dev/reference/as.col_spec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a column specification — as.col_spec","text":"","code":"as.col_spec(\"cccnnn\") #> cols( #> col_character(), #> col_character(), #> col_character(), #> col_number(), #> col_number(), #> col_number() #> )"},{"path":"https://readr.tidyverse.org/dev/reference/callback.html","id":null,"dir":"Reference","previous_headings":"","what":"Callback classes — callback","title":"Callback classes — callback","text":"classes used define callback behaviors.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/callback.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Callback classes — callback","text":"ChunkCallback Callback interface definition, callback functions inherit class. SideEffectChunkCallback Callback function used side effects, results returned. DataFrameCallback Callback function combines result together end. AccumulateCallBack Callback function accumulates single result. Requires parameter acc specify initial value accumulator. parameter acc NULL default.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/callback.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Callback classes — callback","text":"","code":"## If given a regular function it is converted to a SideEffectChunkCallback # view structure of each chunk read_lines_chunked(readr_example(\"mtcars.csv\"), str, chunk_size = 5) #> chr [1:5] \"\\\"mpg\\\",\\\"cyl\\\",\\\"disp\\\",\\\"hp\\\",\\\"drat\\\",\\\"wt\\\",\\\"qsec\\\",\\\"vs\\\",\\\"am\\\",\\\"gear\\\",\\\"carb\\\"\" ... #> chr [1:5] \"18.7,8,360,175,3.15,3.44,17.02,0,0,3,2\" ... #> chr [1:5] \"19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4\" ... #> chr [1:5] \"10.4,8,472,205,2.93,5.25,17.98,0,0,3,4\" ... #> chr [1:5] \"33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1\" ... #> chr [1:5] \"19.2,8,400,175,3.08,3.845,17.05,0,0,3,2\" ... #> chr [1:3] \"19.7,6,145,175,3.62,2.77,15.5,0,1,5,6\" ... #> NULL # Print starting line of each chunk f <- function(x, pos) print(pos) read_lines_chunked(readr_example(\"mtcars.csv\"), SideEffectChunkCallback$new(f), chunk_size = 5) #> [1] 1 #> [1] 6 #> [1] 11 #> [1] 16 #> [1] 21 #> [1] 26 #> [1] 31 #> NULL # If combined results are desired you can use the DataFrameCallback # Cars with 3 gears f <- function(x, pos) subset(x, gear == 3) read_csv_chunked(readr_example(\"mtcars.csv\"), DataFrameCallback$new(f), chunk_size = 5) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> # A tibble: 15 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 2 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 3 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 4 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 5 16.4 8 276. 180 3.07 4.07 17.4 0 0 3 3 #> 6 17.3 8 276. 180 3.07 3.73 17.6 0 0 3 3 #> 7 15.2 8 276. 180 3.07 3.78 18 0 0 3 3 #> 8 10.4 8 472 205 2.93 5.25 18.0 0 0 3 4 #> 9 10.4 8 460 215 3 5.42 17.8 0 0 3 4 #> 10 14.7 8 440 230 3.23 5.34 17.4 0 0 3 4 #> 11 21.5 4 120. 97 3.7 2.46 20.0 1 0 3 1 #> 12 15.5 8 318 150 2.76 3.52 16.9 0 0 3 2 #> 13 15.2 8 304 150 3.15 3.44 17.3 0 0 3 2 #> 14 13.3 8 350 245 3.73 3.84 15.4 0 0 3 4 #> 15 19.2 8 400 175 3.08 3.84 17.0 0 0 3 2 # The ListCallback can be used for more flexible output f <- function(x, pos) x$mpg[x$hp > 100] read_csv_chunked(readr_example(\"mtcars.csv\"), ListCallback$new(f), chunk_size = 5) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> [[1]] #> [1] 21.0 21.0 21.4 18.7 #> #> [[2]] #> [1] 18.1 14.3 19.2 #> #> [[3]] #> [1] 17.8 16.4 17.3 15.2 10.4 #> #> [[4]] #> [1] 10.4 14.7 #> #> [[5]] #> [1] 15.5 15.2 13.3 19.2 #> #> [[6]] #> [1] 30.4 15.8 19.7 #> #> [[7]] #> [1] 15.0 21.4 #> # The AccumulateCallback accumulates results from each chunk f <- function(x, pos, acc) sum(x$mpg) + acc read_csv_chunked(readr_example(\"mtcars.csv\"), AccumulateCallback$new(f, acc = 0), chunk_size = 5) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> [1] 642.9"},{"path":"https://readr.tidyverse.org/dev/reference/clipboard.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns values from the clipboard — clipboard","title":"Returns values from the clipboard — clipboard","text":"useful read_delim() functions read clipboard.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/clipboard.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns values from the clipboard — clipboard","text":"","code":"clipboard()"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/col_skip.html","id":null,"dir":"Reference","previous_headings":"","what":"Skip a column — col_skip","title":"Skip a column — col_skip","text":"Use function ignore column reading file. skip columns otherwise specified, use cols_only().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/col_skip.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Skip a column — col_skip","text":"","code":"col_skip()"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":null,"dir":"Reference","previous_headings":"","what":"Create column specification — cols","title":"Create column specification — cols","text":"cols() includes columns input data, guessing column types default. cols_only() includes columns explicitly specify, skipping rest. general can substitute list() cols() without changing behavior.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create column specification — cols","text":"","code":"cols(..., .default = col_guess()) cols_only(...)"},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create column specification — cols","text":"... Either column objects created col_*(), abbreviated character names (described col_types argument read_delim()). overriding columns, best refer columns name. named, column types must match column names exactly. .default named columns explicitly overridden ... read column type.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Create column specification — cols","text":"available specifications : (string abbreviations brackets) col_logical() [l], containing T, F, TRUE FALSE. col_integer() [], integers. col_double() [d], doubles. col_character() [c], everything else. col_factor(levels, ordered) [f], fixed set values. col_date(format = \"\") [D]: locale's date_format. col_time(format = \"\") [t]: locale's time_format. col_datetime(format = \"\") [T]: ISO8601 date times col_number() [n], numbers containing grouping_mark col_skip() [_, -], import column. col_guess() [?], parse using \"best\" type based input.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/cols.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create column specification — cols","text":"","code":"cols(a = col_integer()) #> cols( #> a = col_integer() #> ) cols_only(a = col_integer()) #> cols_only( #> a = col_integer() #> ) # You can also use the standard abbreviations cols(a = \"i\") #> cols( #> a = col_integer() #> ) cols(a = \"i\", b = \"d\", c = \"_\") #> cols( #> a = col_integer(), #> b = col_double(), #> c = col_skip() #> ) # You can also use multiple sets of column definitions by combining # them like so: t1 <- cols( column_one = col_integer(), column_two = col_number() ) t2 <- cols( column_three = col_character() ) t3 <- t1 t3$cols <- c(t1$cols, t2$cols) t3 #> cols( #> column_one = col_integer(), #> column_two = col_number(), #> column_three = col_character() #> )"},{"path":"https://readr.tidyverse.org/dev/reference/count_fields.html","id":null,"dir":"Reference","previous_headings":"","what":"Count the number of fields in each line of a file — count_fields","title":"Count the number of fields in each line of a file — count_fields","text":"useful diagnosing problems functions fail parse correctly.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/count_fields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Count the number of fields in each line of a file — count_fields","text":"","code":"count_fields(file, tokenizer, skip = 0, n_max = -1L)"},{"path":"https://readr.tidyverse.org/dev/reference/count_fields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Count the number of fields in each line of a file — count_fields","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. tokenizer tokenizer specifies break file fields, e.g., tokenizer_csv(), tokenizer_fwf() skip Number lines skip reading data. n_max Optionally, maximum number rows count fields .","code":""},{"path":"https://readr.tidyverse.org/dev/reference/count_fields.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Count the number of fields in each line of a file — count_fields","text":"","code":"count_fields(readr_example(\"mtcars.csv\"), tokenizer_csv()) #> [1] 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 #> [24] 11 11 11 11 11 11 11 11 11 11"},{"path":"https://readr.tidyverse.org/dev/reference/datasource.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a source object. — datasource","title":"Create a source object. — datasource","text":"Create source object.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/datasource.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a source object. — datasource","text":"","code":"datasource( file, skip = 0, skip_empty_rows = FALSE, comment = \"\", skip_quote = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/datasource.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a source object. — datasource","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. skip Number lines skip reading data.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/datasource.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a source object. — datasource","text":"","code":"# Literal csv datasource(\"a,b,c\\n1,2,3\") #> [[1]] #> [1] \"a,b,c\\n1,2,3\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> attr(,\"class\") #> [1] \"source_string\" \"source\" datasource(charToRaw(\"a,b,c\\n1,2,3\")) #> [[1]] #> [1] 61 2c 62 2c 63 0a 31 2c 32 2c 33 #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> attr(,\"class\") #> [1] \"source_raw\" \"source\" # Strings datasource(readr_example(\"mtcars.csv\")) #> [[1]] #> [1] \"/home/runner/work/_temp/Library/readr/extdata/mtcars.csv\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> attr(,\"class\") #> [1] \"source_file\" \"source\" datasource(readr_example(\"mtcars.csv.bz2\")) #> [[1]] #> [1] \"/tmp/RtmpmWxiqJ/file18471e737c2f\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> $env #> #> #> attr(,\"class\") #> [1] \"source_file\" \"source\" datasource(readr_example(\"mtcars.csv.zip\")) #> [[1]] #> [1] \"/tmp/RtmpmWxiqJ/file184771327078\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> $env #> #> #> attr(,\"class\") #> [1] \"source_file\" \"source\" if (FALSE) { datasource(\"https://github.com/tidyverse/readr/raw/main/inst/extdata/mtcars.csv\") } # Connection con <- rawConnection(charToRaw(\"abc\\n123\")) datasource(con) #> [[1]] #> [1] \"/tmp/RtmpmWxiqJ/file18471cf0107e\" #> #> $skip #> [1] 0 #> #> $skip_empty_rows #> [1] FALSE #> #> $comment #> [1] \"\" #> #> $skip_quote #> [1] TRUE #> #> $env #> #> #> attr(,\"class\") #> [1] \"source_file\" \"source\" close(con)"},{"path":"https://readr.tidyverse.org/dev/reference/date_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Create or retrieve date names — date_names","title":"Create or retrieve date names — date_names","text":"parsing dates, often need know weekdays week months represented text. pair functions allows either create , retrieve standard list. standard list derived ICU (http://site.icu-project.org) via stringi package.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/date_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create or retrieve date names — date_names","text":"","code":"date_names(mon, mon_ab = mon, day, day_ab = day, am_pm = c(\"AM\", \"PM\")) date_names_lang(language) date_names_langs()"},{"path":"https://readr.tidyverse.org/dev/reference/date_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create or retrieve date names — date_names","text":"mon, mon_ab Full abbreviated month names. day, day_ab Full abbreviated week day names. Starts Sunday. am_pm Names used PM. language BCP 47 locale, made language region, e.g. \"en\" American English. See date_names_langs() complete list available locales.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/date_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create or retrieve date names — date_names","text":"","code":"date_names_lang(\"en\") #> #> Days: Sunday (Sun), Monday (Mon), Tuesday (Tue), Wednesday (Wed), #> Thursday (Thu), Friday (Fri), Saturday (Sat) #> Months: January (Jan), February (Feb), March (Mar), April (Apr), May #> (May), June (Jun), July (Jul), August (Aug), September #> (Sep), October (Oct), November (Nov), December (Dec) #> AM/PM: AM/PM date_names_lang(\"ko\") #> #> Days: 일요일 (일), 월요일 (월), 화요일 (화), 수요일 (수), 목요일 (목), #> 금요일 (금), 토요일 (토) #> Months: 1월, 2월, 3월, 4월, 5월, 6월, 7월, 8월, 9월, 10월, 11월, 12월 #> AM/PM: 오전/오후 date_names_lang(\"fr\") #> #> Days: dimanche (dim.), lundi (lun.), mardi (mar.), mercredi (mer.), #> jeudi (jeu.), vendredi (ven.), samedi (sam.) #> Months: janvier (janv.), février (févr.), mars (mars), avril (avr.), mai #> (mai), juin (juin), juillet (juil.), août (août), #> septembre (sept.), octobre (oct.), novembre (nov.), #> décembre (déc.) #> AM/PM: AM/PM"},{"path":"https://readr.tidyverse.org/dev/reference/edition_get.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve the currently active edition — edition_get","title":"Retrieve the currently active edition — edition_get","text":"Retrieve currently active edition","code":""},{"path":"https://readr.tidyverse.org/dev/reference/edition_get.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve the currently active edition — edition_get","text":"","code":"edition_get()"},{"path":"https://readr.tidyverse.org/dev/reference/edition_get.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve the currently active edition — edition_get","text":"integer corresponding currently active edition.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/edition_get.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieve the currently active edition — edition_get","text":"","code":"edition_get() #> [1] 2"},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":null,"dir":"Reference","previous_headings":"","what":"Guess encoding of file — guess_encoding","title":"Guess encoding of file — guess_encoding","text":"Uses stringi::stri_enc_detect(): see documentation caveats.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Guess encoding of file — guess_encoding","text":"","code":"guess_encoding(file, n_max = 10000, threshold = 0.2)"},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Guess encoding of file — guess_encoding","text":"file character string specifying input specified datasource(), raw vector, list raw vectors. n_max Number lines read. n_max -1, lines file read. threshold report guesses threshold certainty.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Guess encoding of file — guess_encoding","text":"tibble","code":""},{"path":"https://readr.tidyverse.org/dev/reference/encoding.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Guess encoding of file — guess_encoding","text":"","code":"guess_encoding(readr_example(\"mtcars.csv\")) #> # A tibble: 1 × 2 #> encoding confidence #> #> 1 ASCII 1 guess_encoding(read_lines_raw(readr_example(\"mtcars.csv\"))) #> # A tibble: 1 × 2 #> encoding confidence #> #> 1 ASCII 1 guess_encoding(read_file_raw(readr_example(\"mtcars.csv\"))) #> # A tibble: 1 × 2 #> encoding confidence #> #> 1 ASCII 1 guess_encoding(\"a\\n\\u00b5\\u00b5\") #> # A tibble: 1 × 2 #> encoding confidence #> #> 1 UTF-8 0.8"},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a data frame to a delimited string — format_delim","title":"Convert a data frame to a delimited string — format_delim","text":"functions equivalent write_csv() etc., instead writing disk, return string.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a data frame to a delimited string — format_delim","text":"","code":"format_delim( x, delim, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", quote_escape = deprecated() ) format_csv( x, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", quote_escape = deprecated() ) format_csv2( x, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", quote_escape = deprecated() ) format_tsv( x, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", quote_escape = deprecated() )"},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a data frame to a delimited string — format_delim","text":"x data frame. delim Delimiter used separate values. Defaults \" \" write_delim(), \",\" write_excel_csv() \";\" write_excel_csv2(). Must single character. na String used missing values. Defaults NA. Missing values never quoted; strings value na always quoted. append FALSE, overwrite existing file. TRUE, append existing file. cases, file exist new file created. col_names FALSE, column names included top file. TRUE, column names included. specified, col_names take opposite value given append. quote handle fields contain characters need quoted. needed - Values quoted needed: contain delimiter, quote, newline. - Quote fields. none - Never quote fields. escape type escape use quotes data. double - quotes escaped doubling . backslash - quotes escaped preceding backslash. none - quotes escaped. eol end line character use. commonly either \"\\n\" Unix style newlines, \"\\r\\n\" Windows style newlines. quote_escape Use escape argument instead.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a data frame to a delimited string — format_delim","text":"string.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"output","dir":"Reference","previous_headings":"","what":"Output","title":"Convert a data frame to a delimited string — format_delim","text":"Factors coerced character. Doubles formatted decimal string using grisu3 algorithm. POSIXct values formatted ISO8601 UTC timezone Note: POSIXct objects local non-UTC timezones converted UTC time writing. columns encoded UTF-8. write_excel_csv() write_excel_csv2() also include UTF-8 Byte order mark indicates Excel csv UTF-8 encoded. write_excel_csv2() write_csv2 created allow users different locale settings save .csv files using default settings (e.g. ; column separator , decimal separator). common European countries. Values quoted contain comma, quote newline. write_*() functions automatically compress outputs appropriate extension given. Three extensions currently supported: .gz gzip compression, .bz2 bzip2 compression .xz lzma compression. See examples information.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Convert a data frame to a delimited string — format_delim","text":"Florian Loitsch, Printing Floating-Point Numbers Quickly Accurately Integers, PLDI '10, http://www.cs.tufts.edu/~nr/cs257/archive/florian-loitsch/printf.pdf","code":""},{"path":"https://readr.tidyverse.org/dev/reference/format_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a data frame to a delimited string — format_delim","text":"","code":"# format_()* functions are useful for testing and reprexes cat(format_csv(mtcars)) #> mpg,cyl,disp,hp,drat,wt,qsec,vs,am,gear,carb #> 21,6,160,110,3.9,2.62,16.46,0,1,4,4 #> 21,6,160,110,3.9,2.875,17.02,0,1,4,4 #> 22.8,4,108,93,3.85,2.32,18.61,1,1,4,1 #> 21.4,6,258,110,3.08,3.215,19.44,1,0,3,1 #> 18.7,8,360,175,3.15,3.44,17.02,0,0,3,2 #> 18.1,6,225,105,2.76,3.46,20.22,1,0,3,1 #> 14.3,8,360,245,3.21,3.57,15.84,0,0,3,4 #> 24.4,4,146.7,62,3.69,3.19,20,1,0,4,2 #> 22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2 #> 19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4 #> 17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4 #> 16.4,8,275.8,180,3.07,4.07,17.4,0,0,3,3 #> 17.3,8,275.8,180,3.07,3.73,17.6,0,0,3,3 #> 15.2,8,275.8,180,3.07,3.78,18,0,0,3,3 #> 10.4,8,472,205,2.93,5.25,17.98,0,0,3,4 #> 10.4,8,460,215,3,5.424,17.82,0,0,3,4 #> 14.7,8,440,230,3.23,5.345,17.42,0,0,3,4 #> 32.4,4,78.7,66,4.08,2.2,19.47,1,1,4,1 #> 30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2 #> 33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1 #> 21.5,4,120.1,97,3.7,2.465,20.01,1,0,3,1 #> 15.5,8,318,150,2.76,3.52,16.87,0,0,3,2 #> 15.2,8,304,150,3.15,3.435,17.3,0,0,3,2 #> 13.3,8,350,245,3.73,3.84,15.41,0,0,3,4 #> 19.2,8,400,175,3.08,3.845,17.05,0,0,3,2 #> 27.3,4,79,66,4.08,1.935,18.9,1,1,4,1 #> 26,4,120.3,91,4.43,2.14,16.7,0,1,5,2 #> 30.4,4,95.1,113,3.77,1.513,16.9,1,1,5,2 #> 15.8,8,351,264,4.22,3.17,14.5,0,1,5,4 #> 19.7,6,145,175,3.62,2.77,15.5,0,1,5,6 #> 15,8,301,335,3.54,3.57,14.6,0,1,5,8 #> 21.4,4,121,109,4.11,2.78,18.6,1,1,4,2 cat(format_tsv(mtcars)) #> mpg\tcyl\tdisp\thp\tdrat\twt\tqsec\tvs\tam\tgear\tcarb #> 21\t6\t160\t110\t3.9\t2.62\t16.46\t0\t1\t4\t4 #> 21\t6\t160\t110\t3.9\t2.875\t17.02\t0\t1\t4\t4 #> 22.8\t4\t108\t93\t3.85\t2.32\t18.61\t1\t1\t4\t1 #> 21.4\t6\t258\t110\t3.08\t3.215\t19.44\t1\t0\t3\t1 #> 18.7\t8\t360\t175\t3.15\t3.44\t17.02\t0\t0\t3\t2 #> 18.1\t6\t225\t105\t2.76\t3.46\t20.22\t1\t0\t3\t1 #> 14.3\t8\t360\t245\t3.21\t3.57\t15.84\t0\t0\t3\t4 #> 24.4\t4\t146.7\t62\t3.69\t3.19\t20\t1\t0\t4\t2 #> 22.8\t4\t140.8\t95\t3.92\t3.15\t22.9\t1\t0\t4\t2 #> 19.2\t6\t167.6\t123\t3.92\t3.44\t18.3\t1\t0\t4\t4 #> 17.8\t6\t167.6\t123\t3.92\t3.44\t18.9\t1\t0\t4\t4 #> 16.4\t8\t275.8\t180\t3.07\t4.07\t17.4\t0\t0\t3\t3 #> 17.3\t8\t275.8\t180\t3.07\t3.73\t17.6\t0\t0\t3\t3 #> 15.2\t8\t275.8\t180\t3.07\t3.78\t18\t0\t0\t3\t3 #> 10.4\t8\t472\t205\t2.93\t5.25\t17.98\t0\t0\t3\t4 #> 10.4\t8\t460\t215\t3\t5.424\t17.82\t0\t0\t3\t4 #> 14.7\t8\t440\t230\t3.23\t5.345\t17.42\t0\t0\t3\t4 #> 32.4\t4\t78.7\t66\t4.08\t2.2\t19.47\t1\t1\t4\t1 #> 30.4\t4\t75.7\t52\t4.93\t1.615\t18.52\t1\t1\t4\t2 #> 33.9\t4\t71.1\t65\t4.22\t1.835\t19.9\t1\t1\t4\t1 #> 21.5\t4\t120.1\t97\t3.7\t2.465\t20.01\t1\t0\t3\t1 #> 15.5\t8\t318\t150\t2.76\t3.52\t16.87\t0\t0\t3\t2 #> 15.2\t8\t304\t150\t3.15\t3.435\t17.3\t0\t0\t3\t2 #> 13.3\t8\t350\t245\t3.73\t3.84\t15.41\t0\t0\t3\t4 #> 19.2\t8\t400\t175\t3.08\t3.845\t17.05\t0\t0\t3\t2 #> 27.3\t4\t79\t66\t4.08\t1.935\t18.9\t1\t1\t4\t1 #> 26\t4\t120.3\t91\t4.43\t2.14\t16.7\t0\t1\t5\t2 #> 30.4\t4\t95.1\t113\t3.77\t1.513\t16.9\t1\t1\t5\t2 #> 15.8\t8\t351\t264\t4.22\t3.17\t14.5\t0\t1\t5\t4 #> 19.7\t6\t145\t175\t3.62\t2.77\t15.5\t0\t1\t5\t6 #> 15\t8\t301\t335\t3.54\t3.57\t14.6\t0\t1\t5\t8 #> 21.4\t4\t121\t109\t4.11\t2.78\t18.6\t1\t1\t4\t2 cat(format_delim(mtcars, \";\")) #> mpg;cyl;disp;hp;drat;wt;qsec;vs;am;gear;carb #> 21;6;160;110;3.9;2.62;16.46;0;1;4;4 #> 21;6;160;110;3.9;2.875;17.02;0;1;4;4 #> 22.8;4;108;93;3.85;2.32;18.61;1;1;4;1 #> 21.4;6;258;110;3.08;3.215;19.44;1;0;3;1 #> 18.7;8;360;175;3.15;3.44;17.02;0;0;3;2 #> 18.1;6;225;105;2.76;3.46;20.22;1;0;3;1 #> 14.3;8;360;245;3.21;3.57;15.84;0;0;3;4 #> 24.4;4;146.7;62;3.69;3.19;20;1;0;4;2 #> 22.8;4;140.8;95;3.92;3.15;22.9;1;0;4;2 #> 19.2;6;167.6;123;3.92;3.44;18.3;1;0;4;4 #> 17.8;6;167.6;123;3.92;3.44;18.9;1;0;4;4 #> 16.4;8;275.8;180;3.07;4.07;17.4;0;0;3;3 #> 17.3;8;275.8;180;3.07;3.73;17.6;0;0;3;3 #> 15.2;8;275.8;180;3.07;3.78;18;0;0;3;3 #> 10.4;8;472;205;2.93;5.25;17.98;0;0;3;4 #> 10.4;8;460;215;3;5.424;17.82;0;0;3;4 #> 14.7;8;440;230;3.23;5.345;17.42;0;0;3;4 #> 32.4;4;78.7;66;4.08;2.2;19.47;1;1;4;1 #> 30.4;4;75.7;52;4.93;1.615;18.52;1;1;4;2 #> 33.9;4;71.1;65;4.22;1.835;19.9;1;1;4;1 #> 21.5;4;120.1;97;3.7;2.465;20.01;1;0;3;1 #> 15.5;8;318;150;2.76;3.52;16.87;0;0;3;2 #> 15.2;8;304;150;3.15;3.435;17.3;0;0;3;2 #> 13.3;8;350;245;3.73;3.84;15.41;0;0;3;4 #> 19.2;8;400;175;3.08;3.845;17.05;0;0;3;2 #> 27.3;4;79;66;4.08;1.935;18.9;1;1;4;1 #> 26;4;120.3;91;4.43;2.14;16.7;0;1;5;2 #> 30.4;4;95.1;113;3.77;1.513;16.9;1;1;5;2 #> 15.8;8;351;264;4.22;3.17;14.5;0;1;5;4 #> 19.7;6;145;175;3.62;2.77;15.5;0;1;5;6 #> 15;8;301;335;3.54;3.57;14.6;0;1;5;8 #> 21.4;4;121;109;4.11;2.78;18.6;1;1;4;2 # Specifying missing values df <- data.frame(x = c(1, NA, 3)) format_csv(df, na = \"missing\") #> [1] \"x\\n1\\nmissing\\n3\\n\" # Quotes are automatically added as needed df <- data.frame(x = c(\"a \", '\"', \",\", \"\\n\")) cat(format_csv(df)) #> x #> a #> \"\"\"\" #> \",\" #> \" #> \""},{"path":"https://readr.tidyverse.org/dev/reference/locale.html","id":null,"dir":"Reference","previous_headings":"","what":"Create locales — locale","title":"Create locales — locale","text":"locale object tries capture defaults can vary countries. set locale , details automatically passed columns parsers. defaults chosen match R (.e. US English) closely possible. See vignette(\"locales\") details.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/locale.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create locales — locale","text":"","code":"locale( date_names = \"en\", date_format = \"%AD\", time_format = \"%AT\", decimal_mark = \".\", grouping_mark = \",\", tz = \"UTC\", encoding = \"UTF-8\", asciify = FALSE ) default_locale()"},{"path":"https://readr.tidyverse.org/dev/reference/locale.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create locales — locale","text":"date_names Character representations day month names. Either language code string (passed date_names_lang()) object created date_names(). date_format, time_format Default date time formats. decimal_mark, grouping_mark Symbols used indicate decimal place, chunk larger numbers. Decimal mark can , .. tz Default tz. used input (time zone present individual strings), output (control default display). default use \"UTC\", time zone use daylight savings time (DST) hence typically useful data. absence time zones makes approximately 50x faster generate UTC times time zone. Use \"\" use system default time zone, beware reproducible across systems. complete list possible time zones, see OlsonNames(). Americans, note \"EST\" Canadian time zone DST. Eastern Standard Time. better use \"US/Eastern\", \"US/Central\" etc. encoding Default encoding. affects file read - readr always converts output UTF-8. asciify diacritics stripped date names converted ASCII? useful dealing ASCII data correct spellings lost. Requires stringi package.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/locale.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create locales — locale","text":"","code":"locale() #> #> Numbers: 123,456.78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: Sunday (Sun), Monday (Mon), Tuesday (Tue), Wednesday (Wed), #> Thursday (Thu), Friday (Fri), Saturday (Sat) #> Months: January (Jan), February (Feb), March (Mar), April (Apr), May #> (May), June (Jun), July (Jul), August (Aug), September #> (Sep), October (Oct), November (Nov), December (Dec) #> AM/PM: AM/PM locale(\"fr\") #> #> Numbers: 123,456.78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: dimanche (dim.), lundi (lun.), mardi (mar.), mercredi (mer.), #> jeudi (jeu.), vendredi (ven.), samedi (sam.) #> Months: janvier (janv.), février (févr.), mars (mars), avril (avr.), mai #> (mai), juin (juin), juillet (juil.), août (août), #> septembre (sept.), octobre (oct.), novembre (nov.), #> décembre (déc.) #> AM/PM: AM/PM # South American locale locale(\"es\", decimal_mark = \",\") #> #> Numbers: 123.456,78 #> Formats: %AD / %AT #> Timezone: UTC #> Encoding: UTF-8 #> #> Days: domingo (dom.), lunes (lun.), martes (mar.), miércoles (mié.), #> jueves (jue.), viernes (vie.), sábado (sáb.) #> Months: enero (ene.), febrero (feb.), marzo (mar.), abril (abr.), mayo #> (may.), junio (jun.), julio (jul.), agosto (ago.), #> septiembre (sept.), octubre (oct.), noviembre (nov.), #> diciembre (dic.) #> AM/PM: a. m./p. m."},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"function superseded readr moved meltr package.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"","code":"melt_delim( file, delim, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE ) melt_csv( file, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE ) melt_csv2( file, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE ) melt_tsv( file, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. delim Single character used separate fields within record. quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. n_max Maximum number lines read. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"tibble() four columns: row, row token comes original file col, column token comes original file data_type, data type token, e.g. \"integer\", \"character\", \"date\", guessed similar way guess_parser() function. value, token character string, unchanged representation original file. parsing problems, warning tells many, can retrieve details problems().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"certain non-rectangular data formats, can useful parse data melted format row represents single token. melt_csv() melt_tsv() special cases general melt_delim(). useful reading common types flat file data, comma separated values tab separated values, respectively. melt_csv2() uses ; field separator , decimal point. common European countries.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return melted data for each token in a delimited file (including csv & tsv) — melt_delim","text":"","code":"# Input sources ------------------------------------------------------------- # Read from a path melt_csv(readr_example(\"mtcars.csv\")) #> Warning: `melt_csv()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_csv()` instead #> # A tibble: 363 × 4 #> row col data_type value #> #> 1 1 1 character mpg #> 2 1 2 character cyl #> 3 1 3 character disp #> 4 1 4 character hp #> 5 1 5 character drat #> 6 1 6 character wt #> 7 1 7 character qsec #> 8 1 8 character vs #> 9 1 9 character am #> 10 1 10 character gear #> # ℹ 353 more rows melt_csv(readr_example(\"mtcars.csv.zip\")) #> # A tibble: 363 × 4 #> row col data_type value #> #> 1 1 1 character mpg #> 2 1 2 character cyl #> 3 1 3 character disp #> 4 1 4 character hp #> 5 1 5 character drat #> 6 1 6 character wt #> 7 1 7 character qsec #> 8 1 8 character vs #> 9 1 9 character am #> 10 1 10 character gear #> # ℹ 353 more rows melt_csv(readr_example(\"mtcars.csv.bz2\")) #> # A tibble: 363 × 4 #> row col data_type value #> #> 1 1 1 character mpg #> 2 1 2 character cyl #> 3 1 3 character disp #> 4 1 4 character hp #> 5 1 5 character drat #> 6 1 6 character wt #> 7 1 7 character qsec #> 8 1 8 character vs #> 9 1 9 character am #> 10 1 10 character gear #> # ℹ 353 more rows if (FALSE) { melt_csv(\"https://github.com/tidyverse/readr/raw/main/inst/extdata/mtcars.csv\") } # Or directly from a string (must contain a newline) melt_csv(\"x,y\\n1,2\\n3,4\") #> # A tibble: 6 × 4 #> row col data_type value #> #> 1 1 1 character x #> 2 1 2 character y #> 3 2 1 integer 1 #> 4 2 2 integer 2 #> 5 3 1 integer 3 #> 6 3 2 integer 4 # To import empty cells as 'empty' rather than `NA` melt_csv(\"x,y\\n,NA,\\\"\\\",''\", na = \"NA\") #> # A tibble: 6 × 4 #> row col data_type value #> #> 1 1 1 character \"x\" #> 2 1 2 character \"y\" #> 3 2 1 empty \"\" #> 4 2 2 missing NA #> 5 2 3 empty \"\" #> 6 2 4 character \"''\" # File types ---------------------------------------------------------------- melt_csv(\"a,b\\n1.0,2.0\") #> # A tibble: 4 × 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 2 1 double 1.0 #> 4 2 2 double 2.0 melt_csv2(\"a;b\\n1,0;2,0\") #> Warning: `melt_csv2()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_csv2()` instead #> ℹ Using \"','\" as decimal and \"'.'\" as grouping mark. Use `read_delim()` for more control. #> # A tibble: 4 × 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 2 1 double 1,0 #> 4 2 2 double 2,0 melt_tsv(\"a\\tb\\n1.0\\t2.0\") #> Warning: `melt_tsv()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_tsv()` instead #> # A tibble: 4 × 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 2 1 double 1.0 #> 4 2 2 double 2.0 melt_delim(\"a|b\\n1.0|2.0\", delim = \"|\") #> Warning: `melt_delim()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_delim()` instead #> # A tibble: 4 × 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 2 1 double 1.0 #> 4 2 2 double 2.0"},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":null,"dir":"Reference","previous_headings":"","what":"Melt a delimited file by chunks — melt_delim_chunked","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"certain non-rectangular data formats, can useful parse data melted format row represents single token.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"","code":"melt_delim_chunked( file, callback, chunk_size = 10000, delim, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, progress = show_progress(), skip_empty_rows = FALSE ) melt_csv_chunked( file, callback, chunk_size = 10000, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, progress = show_progress(), skip_empty_rows = FALSE ) melt_csv2_chunked( file, callback, chunk_size = 10000, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, progress = show_progress(), skip_empty_rows = FALSE ) melt_tsv_chunked( file, callback, chunk_size = 10000, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, progress = show_progress(), skip_empty_rows = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. callback callback function call chunk chunk_size number rows include chunk delim Single character used separate fields within record. quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"melt_delim_chunked() specialisations melt_csv_chunked(), melt_csv2_chunked() melt_tsv_chunked() read files chunk rows time, executing given function one chunk reading next.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/melt_delim_chunked.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Melt a delimited file by chunks — melt_delim_chunked","text":"","code":"# Cars with 3 gears f <- function(x, pos) subset(x, data_type == \"integer\") melt_csv_chunked(readr_example(\"mtcars.csv\"), DataFrameCallback$new(f), chunk_size = 5) #> # A tibble: 218 × 4 #> row col data_type value #> #> 1 2 1 integer 21 #> 2 2 2 integer 6 #> 3 2 3 integer 160 #> 4 2 4 integer 110 #> 5 2 8 integer 0 #> 6 2 9 integer 1 #> 7 2 10 integer 4 #> 8 2 11 integer 4 #> 9 3 1 integer 21 #> 10 3 2 integer 6 #> # ℹ 208 more rows"},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":null,"dir":"Reference","previous_headings":"","what":"Return melted data for each token in a fixed width file — melt_fwf","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"function superseded readr moved meltr package.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"","code":"melt_fwf( file, col_positions, locale = default_locale(), na = c(\"\", \"NA\"), comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, progress = show_progress(), skip_empty_rows = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. col_positions Column positions, created fwf_empty(), fwf_widths() fwf_positions(). read selected fields, use fwf_positions(). width last column variable (ragged fwf file), supply last end position NA. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. n_max Maximum number lines read. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"certain non-rectangular data formats, can useful parse data melted format row represents single token. melt_fwf() parses token fixed width file single row, still requires field every row source file.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/melt_fwf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return melted data for each token in a fixed width file — melt_fwf","text":"","code":"fwf_sample <- readr_example(\"fwf-sample.txt\") cat(read_lines(fwf_sample)) #> John Smith WA 418-Y11-4111 Mary Hartford CA 319-Z19-4341 Evan Nolan IL 219-532-c301 # You can specify column positions in several ways: # 1. Guess based on position of empty columns melt_fwf(fwf_sample, fwf_empty(fwf_sample, col_names = c(\"first\", \"last\", \"state\", \"ssn\"))) #> Warning: `melt_fwf()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_fwf()` instead #> # A tibble: 12 × 4 #> row col data_type value #> #> 1 1 1 character John #> 2 1 2 character Smith #> 3 1 3 character WA #> 4 1 4 character 418-Y11-4111 #> 5 2 1 character Mary #> 6 2 2 character Hartford #> 7 2 3 character CA #> 8 2 4 character 319-Z19-4341 #> 9 3 1 character Evan #> 10 3 2 character Nolan #> 11 3 3 character IL #> 12 3 4 character 219-532-c301 # 2. A vector of field widths melt_fwf(fwf_sample, fwf_widths(c(20, 10, 12), c(\"name\", \"state\", \"ssn\"))) #> # A tibble: 9 × 4 #> row col data_type value #> #> 1 1 1 character John Smith #> 2 1 2 character WA #> 3 1 3 character 418-Y11-4111 #> 4 2 1 character Mary Hartford #> 5 2 2 character CA #> 6 2 3 character 319-Z19-4341 #> 7 3 1 character Evan Nolan #> 8 3 2 character IL #> 9 3 3 character 219-532-c301 # 3. Paired vectors of start and end positions melt_fwf(fwf_sample, fwf_positions(c(1, 30), c(10, 42), c(\"name\", \"ssn\"))) #> # A tibble: 6 × 4 #> row col data_type value #> #> 1 1 1 character John Smith #> 2 1 2 character 418-Y11-4111 #> 3 2 1 character Mary Hartf #> 4 2 2 character 319-Z19-4341 #> 5 3 1 character Evan Nolan #> 6 3 2 character 219-532-c301 # 4. Named arguments with start and end positions melt_fwf(fwf_sample, fwf_cols(name = c(1, 10), ssn = c(30, 42))) #> # A tibble: 6 × 4 #> row col data_type value #> #> 1 1 1 character John Smith #> 2 1 2 character 418-Y11-4111 #> 3 2 1 character Mary Hartf #> 4 2 2 character 319-Z19-4341 #> 5 3 1 character Evan Nolan #> 6 3 2 character 219-532-c301 # 5. Named arguments with column widths melt_fwf(fwf_sample, fwf_cols(name = 20, state = 10, ssn = 12)) #> # A tibble: 9 × 4 #> row col data_type value #> #> 1 1 1 character John Smith #> 2 1 2 character WA #> 3 1 3 character 418-Y11-4111 #> 4 2 1 character Mary Hartford #> 5 2 2 character CA #> 6 2 3 character 319-Z19-4341 #> 7 3 1 character Evan Nolan #> 8 3 2 character IL #> 9 3 3 character 219-532-c301"},{"path":"https://readr.tidyverse.org/dev/reference/melt_table.html","id":null,"dir":"Reference","previous_headings":"","what":"Return melted data for each token in a whitespace-separated file — melt_table","title":"Return melted data for each token in a whitespace-separated file — melt_table","text":"function superseded readr moved meltr package. certain non-rectangular data formats, can useful parse data melted format row represents single token. melt_table() melt_table2() designed read type textual data column separated one () columns space. melt_table2() allows number whitespace characters columns, lines can different lengths. melt_table() strict, line must length, field position every line. first finds empty columns parses like fixed width file.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/melt_table.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return melted data for each token in a whitespace-separated file — melt_table","text":"","code":"melt_table( file, locale = default_locale(), na = \"NA\", skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress(), comment = \"\", skip_empty_rows = FALSE ) melt_table2( file, locale = default_locale(), na = \"NA\", skip = 0, n_max = Inf, progress = show_progress(), comment = \"\", skip_empty_rows = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/melt_table.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return melted data for each token in a whitespace-separated file — melt_table","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. skip Number lines skip reading data. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. comment string used identify comments. text comment characters silently ignored. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/melt_table.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return melted data for each token in a whitespace-separated file — melt_table","text":"","code":"fwf <- readr_example(\"fwf-sample.txt\") writeLines(read_lines(fwf)) #> John Smith WA 418-Y11-4111 #> Mary Hartford CA 319-Z19-4341 #> Evan Nolan IL 219-532-c301 melt_table(fwf) #> Warning: `melt_table()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_table()` instead #> # A tibble: 12 × 4 #> row col data_type value #> #> 1 1 1 character John #> 2 1 2 character Smith #> 3 1 3 character WA #> 4 1 4 character 418-Y11-4111 #> 5 2 1 character Mary #> 6 2 2 character Hartford #> 7 2 3 character CA #> 8 2 4 character 319-Z19-4341 #> 9 3 1 character Evan #> 10 3 2 character Nolan #> 11 3 3 character IL #> 12 3 4 character 219-532-c301 ws <- readr_example(\"whitespace-sample.txt\") writeLines(read_lines(ws)) #> first last state phone #> John Smith WA 418-Y11-4111 #> Mary Hartford CA 319-Z19-4341 #> Evan Nolan IL 219-532-c301 melt_table2(ws) #> Warning: `melt_table2()` was deprecated in readr 2.0.0. #> ℹ Please use `meltr::melt_table2()` instead #> # A tibble: 16 × 4 #> row col data_type value #> #> 1 1 1 character first #> 2 1 2 character last #> 3 1 3 character state #> 4 1 4 character phone #> 5 2 1 character John #> 6 2 2 character Smith #> 7 2 3 character WA #> 8 2 4 character 418-Y11-4111 #> 9 3 1 character Mary #> 10 3 2 character Hartford #> 11 3 3 character CA #> 12 3 4 character 319-Z19-4341 #> 13 4 1 character Evan #> 14 4 2 character Nolan #> 15 4 3 character IL #> 16 4 4 character 219-532-c301"},{"path":"https://readr.tidyverse.org/dev/reference/output_column.html","id":null,"dir":"Reference","previous_headings":"","what":"Preprocess column for output — output_column","title":"Preprocess column for output — output_column","text":"generic function applied column saved disk. provides hook S3 classes need special handling.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/output_column.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Preprocess column for output — output_column","text":"","code":"output_column(x, name)"},{"path":"https://readr.tidyverse.org/dev/reference/output_column.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Preprocess column for output — output_column","text":"x vector","code":""},{"path":"https://readr.tidyverse.org/dev/reference/output_column.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Preprocess column for output — output_column","text":"","code":"# Most columns are not altered, but POSIXct are converted to ISO8601. x <- parse_datetime(\"2016-01-01\") str(output_column(x)) #> chr \"2016-01-01T00:00:00Z\""},{"path":"https://readr.tidyverse.org/dev/reference/parse_atomic.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse logicals, integers, and reals — parse_atomic","title":"Parse logicals, integers, and reals — parse_atomic","text":"Use parse_*() character vector want parse. Use col_*() conjunction read_*() function parse values read .","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_atomic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse logicals, integers, and reals — parse_atomic","text":"","code":"parse_logical(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) parse_integer(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) parse_double(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) parse_character(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) col_logical() col_integer() col_double() col_character()"},{"path":"https://readr.tidyverse.org/dev/reference/parse_atomic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse logicals, integers, and reals — parse_atomic","text":"x Character vector values parse. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_atomic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse logicals, integers, and reals — parse_atomic","text":"","code":"parse_integer(c(\"1\", \"2\", \"3\")) #> [1] 1 2 3 parse_double(c(\"1\", \"2\", \"3.123\")) #> [1] 1.000 2.000 3.123 parse_number(\"$1,123,456.00\") #> [1] 1123456 # Use locale to override default decimal and grouping marks es_MX <- locale(\"es\", decimal_mark = \",\") parse_number(\"$1.123.456,00\", locale = es_MX) #> [1] 1123456 # Invalid values are replaced with missing values with a warning. x <- c(\"1\", \"2\", \"3\", \"-\") parse_double(x) #> Warning: 1 parsing failure. #> row col expected actual #> 4 -- a double - #> [1] 1 2 3 NA #> attr(,\"problems\") #> # A tibble: 1 × 4 #> row col expected actual #> #> 1 4 NA a double - # Or flag values as missing parse_double(x, na = \"-\") #> [1] 1 2 3 NA"},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse date/times — parse_datetime","title":"Parse date/times — parse_datetime","text":"Parse date/times","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse date/times — parse_datetime","text":"","code":"parse_datetime( x, format = \"\", na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE ) parse_date( x, format = \"\", na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE ) parse_time( x, format = \"\", na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE ) col_datetime(format = \"\") col_date(format = \"\") col_time(format = \"\")"},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse date/times — parse_datetime","text":"x character vector dates parse. format format specification, described . set \"\", date times parsed ISO8601, dates times used date time formats specified locale(). Unlike strptime(), format specification must match complete string. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Parse date/times — parse_datetime","text":"POSIXct() vector tzone attribute set tz. Elements parsed (generate valid dates) set NA, warning message inform total number failures.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"format-specification","dir":"Reference","previous_headings":"","what":"Format specification","title":"Parse date/times — parse_datetime","text":"readr uses format specification similar strptime(). three types element: Date components specified \"%\" followed letter. example \"%Y\" matches 4 digit year, \"%m\", matches 2 digit month \"%d\" matches 2 digit day. Month day default 1, (.e. Jan 1st) present, example year given. Whitespace sequence zero whitespace characters. character matched exactly. parse_datetime() recognises following format specifications: Year: \"%Y\" (4 digits). \"%y\" (2 digits); 00-69 -> 2000-2069, 70-99 -> 1970-1999. Month: \"%m\" (2 digits), \"%b\" (abbreviated name current locale), \"%B\" (full name current locale). Day: \"%d\" (2 digits), \"%e\" (optional leading space), \"%\" (abbreviated name current locale). Hour: \"%H\" \"%\" \"%h\", use (H) /PM, use h (H) times represent durations longer one day. Minutes: \"%M\" Seconds: \"%S\" (integer seconds), \"%OS\" (partial seconds) Time zone: \"%Z\" (name, e.g. \"America/Chicago\"), \"%z\" (offset UTC, e.g. \"+0800\") /PM indicator: \"%p\". Non-digits: \"%.\" skips one non-digit character, \"%+\" skips one non-digit characters, \"%*\" skips number non-digits characters. Automatic parsers: \"%AD\" parses flexible YMD parser, \"%\" parses flexible HMS parser. Time since Unix epoch: \"%s\" decimal seconds since Unix epoch. Shortcuts: \"%D\" = \"%m/%d/%y\", \"%F\" = \"%Y-%m-%d\", \"%R\" = \"%H:%M\", \"%T\" = \"%H:%M:%S\", \"%x\" = \"%y/%m/%d\".","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"iso-support","dir":"Reference","previous_headings":"","what":"ISO8601 support","title":"Parse date/times — parse_datetime","text":"Currently, readr support ISO8601. Missing features: Week & weekday specifications, e.g. \"2013-W05\", \"2013-W05-10\". Ordinal dates, e.g. \"2013-095\". Using commas instead period decimal separator. parser also little laxer ISO8601: Dates times can separated space, just T. Mostly correct specifications like \"2009-05-19 14:\" \"200912-01\" work.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_datetime.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse date/times — parse_datetime","text":"","code":"# Format strings -------------------------------------------------------- parse_datetime(\"01/02/2010\", \"%d/%m/%Y\") #> [1] \"2010-02-01 UTC\" parse_datetime(\"01/02/2010\", \"%m/%d/%Y\") #> [1] \"2010-01-02 UTC\" # Handle any separator parse_datetime(\"01/02/2010\", \"%m%.%d%.%Y\") #> [1] \"2010-01-02 UTC\" # Dates look the same, but internally they use the number of days since # 1970-01-01 instead of the number of seconds. This avoids a whole lot # of troubles related to time zones, so use if you can. parse_date(\"01/02/2010\", \"%d/%m/%Y\") #> [1] \"2010-02-01\" parse_date(\"01/02/2010\", \"%m/%d/%Y\") #> [1] \"2010-01-02\" # You can parse timezones from strings (as listed in OlsonNames()) parse_datetime(\"2010/01/01 12:00 US/Central\", \"%Y/%m/%d %H:%M %Z\") #> [1] \"2010-01-01 18:00:00 UTC\" # Or from offsets parse_datetime(\"2010/01/01 12:00 -0600\", \"%Y/%m/%d %H:%M %z\") #> [1] \"2010-01-01 18:00:00 UTC\" # Use the locale parameter to control the default time zone # (but note UTC is considerably faster than other options) parse_datetime(\"2010/01/01 12:00\", \"%Y/%m/%d %H:%M\", locale = locale(tz = \"US/Central\") ) #> [1] \"2010-01-01 12:00:00 CST\" parse_datetime(\"2010/01/01 12:00\", \"%Y/%m/%d %H:%M\", locale = locale(tz = \"US/Eastern\") ) #> [1] \"2010-01-01 12:00:00 EST\" # Unlike strptime, the format specification must match the complete # string (ignoring leading and trailing whitespace). This avoids common # errors: strptime(\"01/02/2010\", \"%d/%m/%y\") #> [1] \"2020-02-01 UTC\" parse_datetime(\"01/02/2010\", \"%d/%m/%y\") #> Warning: 1 parsing failure. #> row col expected actual #> 1 -- date like %d/%m/%y 01/02/2010 #> [1] NA # Failures ------------------------------------------------------------- parse_datetime(\"01/01/2010\", \"%d/%m/%Y\") #> [1] \"2010-01-01 UTC\" parse_datetime(c(\"01/ab/2010\", \"32/01/2010\"), \"%d/%m/%Y\") #> Warning: 2 parsing failures. #> row col expected actual #> 1 -- date like %d/%m/%Y 01/ab/2010 #> 2 -- valid date 32/01/2010 #> [1] NA NA # Locales -------------------------------------------------------------- # By default, readr expects English date/times, but that's easy to change' parse_datetime(\"1 janvier 2015\", \"%d %B %Y\", locale = locale(\"fr\")) #> [1] \"2015-01-01 UTC\" parse_datetime(\"1 enero 2015\", \"%d %B %Y\", locale = locale(\"es\")) #> [1] \"2015-01-01 UTC\" # ISO8601 -------------------------------------------------------------- # With separators parse_datetime(\"1979-10-14\") #> [1] \"1979-10-14 UTC\" parse_datetime(\"1979-10-14T10\") #> [1] \"1979-10-14 10:00:00 UTC\" parse_datetime(\"1979-10-14T10:11\") #> [1] \"1979-10-14 10:11:00 UTC\" parse_datetime(\"1979-10-14T10:11:12\") #> [1] \"1979-10-14 10:11:12 UTC\" parse_datetime(\"1979-10-14T10:11:12.12345\") #> [1] \"1979-10-14 10:11:12 UTC\" # Without separators parse_datetime(\"19791014\") #> [1] \"1979-10-14 UTC\" parse_datetime(\"19791014T101112\") #> [1] \"1979-10-14 10:11:12 UTC\" # Time zones us_central <- locale(tz = \"US/Central\") parse_datetime(\"1979-10-14T1010\", locale = us_central) #> [1] \"1979-10-14 10:10:00 CDT\" parse_datetime(\"1979-10-14T1010-0500\", locale = us_central) #> [1] \"1979-10-14 10:10:00 CDT\" parse_datetime(\"1979-10-14T1010Z\", locale = us_central) #> [1] \"1979-10-14 05:10:00 CDT\" # Your current time zone parse_datetime(\"1979-10-14T1010\", locale = locale(tz = \"\")) #> [1] \"1979-10-14 10:10:00 UTC\""},{"path":"https://readr.tidyverse.org/dev/reference/parse_factor.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse factors — parse_factor","title":"Parse factors — parse_factor","text":"parse_factor() similar factor(), generates warning levels specified elements x found levels.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_factor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse factors — parse_factor","text":"","code":"parse_factor( x, levels = NULL, ordered = FALSE, na = c(\"\", \"NA\"), locale = default_locale(), include_na = TRUE, trim_ws = TRUE ) col_factor(levels = NULL, ordered = FALSE, include_na = FALSE)"},{"path":"https://readr.tidyverse.org/dev/reference/parse_factor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse factors — parse_factor","text":"x Character vector values parse. levels Character vector allowed levels. levels = NULL (default), levels discovered unique values x, order appear x. ordered ordered factor? na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. include_na TRUE x contains least one NA, NA included levels constructed factor. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_factor.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse factors — parse_factor","text":"","code":"# discover the levels from the data parse_factor(c(\"a\", \"b\")) #> [1] a b #> Levels: a b parse_factor(c(\"a\", \"b\", \"-99\")) #> [1] a b -99 #> Levels: a b -99 parse_factor(c(\"a\", \"b\", \"-99\"), na = c(\"\", \"NA\", \"-99\")) #> [1] a b #> Levels: a b parse_factor(c(\"a\", \"b\", \"-99\"), na = c(\"\", \"NA\", \"-99\"), include_na = FALSE) #> [1] a b #> Levels: a b # provide the levels explicitly parse_factor(c(\"a\", \"b\"), levels = letters[1:5]) #> [1] a b #> Levels: a b c d e x <- c(\"cat\", \"dog\", \"caw\") animals <- c(\"cat\", \"dog\", \"cow\") # base::factor() silently converts elements that do not match any levels to # NA factor(x, levels = animals) #> [1] cat dog #> Levels: cat dog cow # parse_factor() generates same factor as base::factor() but throws a warning # and reports problems parse_factor(x, levels = animals) #> Warning: 1 parsing failure. #> row col expected actual #> 3 -- value in level set caw #> [1] cat dog #> attr(,\"problems\") #> # A tibble: 1 × 4 #> row col expected actual #> #> 1 3 NA value in level set caw #> Levels: cat dog cow"},{"path":"https://readr.tidyverse.org/dev/reference/parse_guess.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse using the ","title":"Parse using the ","text":"parse_guess() returns parser vector; guess_parser() returns name parser. functions use number heuristics determine type vector \"best\". Generally try err side safety, straightforward override parsing choice needed.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_guess.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse using the ","text":"","code":"parse_guess( x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE, guess_integer = FALSE ) col_guess() guess_parser( x, locale = default_locale(), guess_integer = FALSE, na = c(\"\", \"NA\") )"},{"path":"https://readr.tidyverse.org/dev/reference/parse_guess.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse using the ","text":"x Character vector values parse. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? guess_integer TRUE, guess integer types whole numbers, FALSE guess numeric type numbers.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_guess.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse using the ","text":"","code":"# Logical vectors parse_guess(c(\"FALSE\", \"TRUE\", \"F\", \"T\")) #> [1] FALSE TRUE FALSE TRUE # Integers and doubles parse_guess(c(\"1\", \"2\", \"3\")) #> [1] 1 2 3 parse_guess(c(\"1.6\", \"2.6\", \"3.4\")) #> [1] 1.6 2.6 3.4 # Numbers containing grouping mark guess_parser(\"1,234,566\") #> [1] \"number\" parse_guess(\"1,234,566\") #> [1] 1234566 # ISO 8601 date times guess_parser(c(\"2010-10-10\")) #> [1] \"date\" parse_guess(c(\"2010-10-10\")) #> [1] \"2010-10-10\""},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse numbers, flexibly — parse_number","title":"Parse numbers, flexibly — parse_number","text":"parses first number finds, dropping non-numeric characters first number characters first number. grouping mark specified locale ignored inside number.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse numbers, flexibly — parse_number","text":"","code":"parse_number(x, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE) col_number()"},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse numbers, flexibly — parse_number","text":"x Character vector values parse. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Parse numbers, flexibly — parse_number","text":"numeric vector (double) parsed numbers.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_number.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse numbers, flexibly — parse_number","text":"","code":"## These all return 1000 parse_number(\"$1,000\") ## leading `$` and grouping character `,` ignored #> [1] 1000 parse_number(\"euro1,000\") ## leading non-numeric euro ignored #> [1] 1000 parse_number(\"t1000t1000\") ## only parses first number found #> [1] 1000 parse_number(\"1,234.56\") #> [1] 1234.56 ## explicit locale specifying European grouping and decimal marks parse_number(\"1.234,56\", locale = locale(decimal_mark = \",\", grouping_mark = \".\")) #> [1] 1234.56 ## SI/ISO 31-0 standard spaces for number grouping parse_number(\"1 234.56\", locale = locale(decimal_mark = \".\", grouping_mark = \" \")) #> [1] 1234.56 ## Specifying strings for NAs parse_number(c(\"1\", \"2\", \"3\", \"NA\")) #> [1] 1 2 3 NA parse_number(c(\"1\", \"2\", \"3\", \"NA\", \"Nothing\"), na = c(\"NA\", \"Nothing\")) #> [1] 1 2 3 NA NA"},{"path":"https://readr.tidyverse.org/dev/reference/parse_vector.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse a character vector. — parse_vector","title":"Parse a character vector. — parse_vector","text":"Parse character vector.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/parse_vector.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse a character vector. — parse_vector","text":"","code":"parse_vector( x, collector, na = c(\"\", \"NA\"), locale = default_locale(), trim_ws = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/parse_vector.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse a character vector. — parse_vector","text":"x Character vector elements parse. collector Column specification. na Character vector strings interpret missing values. Set option character() indicate missing values. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ?","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/parse_vector.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse a character vector. — parse_vector","text":"","code":"x <- c(\"1\", \"2\", \"3\", \"NA\") parse_vector(x, col_integer()) #> [1] 1 2 3 NA parse_vector(x, col_double()) #> [1] 1 2 3 NA"},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve parsing problems — problems","title":"Retrieve parsing problems — problems","text":"Readr functions throw error parsing fails unrecoverable way. However, lots potential problems might want know - stored problems attribute output, can easily access function. stop_for_problems() throw error parsing problems: useful automated scripts want throw error soon encounter problem.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve parsing problems — problems","text":"","code":"problems(x = .Last.value) stop_for_problems(x)"},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve parsing problems — problems","text":"x data frame (read_*()) vector (parse_*()).","code":""},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve parsing problems — problems","text":"data frame one row problem four columns: row,col Row column problem expected readr expected find actual actually got","code":""},{"path":"https://readr.tidyverse.org/dev/reference/problems.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Retrieve parsing problems — problems","text":"","code":"x <- parse_integer(c(\"1X\", \"blah\", \"3\")) #> Warning: 2 parsing failures. #> row col expected actual #> 1 -- no trailing characters 1X #> 2 -- no trailing characters blah problems(x) #> # A tibble: 2 × 4 #> row col expected actual #> #> 1 1 NA no trailing characters 1X #> 2 2 NA no trailing characters blah y <- parse_integer(c(\"1\", \"2\", \"3\")) problems(y)"},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":null,"dir":"Reference","previous_headings":"","what":"Read built-in object from package — read_builtin","title":"Read built-in object from package — read_builtin","text":"Consistent wrapper around data() forces promise. also stronger parallel loading data file.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read built-in object from package — read_builtin","text":"","code":"read_builtin(x, package = NULL)"},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read built-in object from package — read_builtin","text":"x Name (character string) data set read. package Name package find data set. default, attached packages searched 'data' subdirectory (present) current working directory.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read built-in object from package — read_builtin","text":"object built-class x.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_builtin.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read built-in object from package — read_builtin","text":"","code":"read_builtin(\"mtcars\", \"datasets\") #> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2"},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"read_csv() read_tsv() special cases general read_delim(). useful reading common types flat file data, comma separated values tab separated values, respectively. read_csv2() uses ; field separator , decimal point. format common European countries.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"","code":"read_delim( file, delim = NULL, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, col_names = TRUE, col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), name_repair = \"unique\", num_threads = readr_threads(), progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) read_csv( file, col_names = TRUE, col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), name_repair = \"unique\", num_threads = readr_threads(), progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) read_csv2( file, col_names = TRUE, col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) read_tsv( file, col_names = TRUE, col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(1000, n_max), progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() )"},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. delim Single character used separate fields within record. quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). col_select Columns include results. can use mini-language dplyr::select() refer columns name. Use c() use one selection expression. Although usage less common, col_select also accepts numeric column index. See ?tidyselect::language full details selection language. id name column store file path. useful reading multiple input files data file paths, data collection date. NULL (default) extra column created. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. name_repair Handling column names. default behaviour ensure column names \"unique\". Various repair strategies supported: \"minimal\": name repair checks, beyond basic existence names. \"unique\" (default value): Make sure names unique empty. \"check_unique\": name repair, check unique. \"unique_quiet\": Repair unique strategy, quietly. \"universal\": Make names unique syntactic. \"universal_quiet\": Repair universal strategy, quietly. function: Apply custom name repair (e.g., name_repair = make.names names style base R). purrr-style anonymous function, see rlang::as_function(). argument passed repair vctrs::vec_as_names(). See details terms strategies used enforce . num_threads number processing threads use initial parsing lazy reading data. data contains newlines within fields parser automatically detect fall back using one thread . However know file newlines within quoted fields safest set num_threads = 1 explicitly. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. lazy Read values lazily? default, FALSE, special considerations reading file lazily tripped users. Specifically, things get tricky reading writing back file. , general, lazy reading (lazy = TRUE) many benefits, especially interactive use downstream work involves subset rows columns. Learn should_read_lazy() documentation altrep argument vroom::vroom().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"tibble(). parsing problems, warning alert . can retrieve full details calling problems() dataset.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read a delimited file (including CSV and TSV) into a tibble — read_delim","text":"","code":"# Input sources ------------------------------------------------------------- # Read from a path read_csv(readr_example(\"mtcars.csv\")) #> Rows: 32 Columns: 11 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 32 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows read_csv(readr_example(\"mtcars.csv.zip\")) #> Rows: 32 Columns: 11 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 32 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows read_csv(readr_example(\"mtcars.csv.bz2\")) #> Rows: 32 Columns: 11 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 32 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows if (FALSE) { # Including remote paths read_csv(\"https://github.com/tidyverse/readr/raw/main/inst/extdata/mtcars.csv\") } # Read from multiple file paths at once continents <- c(\"africa\", \"americas\", \"asia\", \"europe\", \"oceania\") filepaths <- vapply( paste0(\"mini-gapminder-\", continents, \".csv\"), FUN = readr_example, FUN.VALUE = character(1) ) read_csv(filepaths, id = \"file\") #> Rows: 26 Columns: 6 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (1): country #> dbl (4): year, lifeExp, pop, gdpPercap #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 26 × 6 #> file country year lifeExp pop gdpPercap #> #> 1 /home/runner/work/_temp/Library… Algeria 1952 43.1 9.28e6 2449. #> 2 /home/runner/work/_temp/Library… Angola 1952 30.0 4.23e6 3521. #> 3 /home/runner/work/_temp/Library… Benin 1952 38.2 1.74e6 1063. #> 4 /home/runner/work/_temp/Library… Botswa… 1952 47.6 4.42e5 851. #> 5 /home/runner/work/_temp/Library… Burkin… 1952 32.0 4.47e6 543. #> 6 /home/runner/work/_temp/Library… Burundi 1952 39.0 2.45e6 339. #> 7 /home/runner/work/_temp/Library… Argent… 1952 62.5 1.79e7 5911. #> 8 /home/runner/work/_temp/Library… Bolivia 1952 40.4 2.88e6 2677. #> 9 /home/runner/work/_temp/Library… Brazil 1952 50.9 5.66e7 2109. #> 10 /home/runner/work/_temp/Library… Canada 1952 68.8 1.48e7 11367. #> # ℹ 16 more rows # Or directly from a string with `I()` read_csv(I(\"x,y\\n1,2\\n3,4\")) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x, y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x y #> #> 1 1 2 #> 2 3 4 # Column selection----------------------------------------------------------- # Pass column names or indexes directly to select them read_csv(readr_example(\"chickens.csv\"), col_select = c(chicken, eggs_laid)) #> Rows: 5 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (1): chicken #> dbl (1): eggs_laid #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 2 #> chicken eggs_laid #> #> 1 Foghorn Leghorn 0 #> 2 Chicken Little 3 #> 3 Ginger 12 #> 4 Camilla the Chicken 7 #> 5 Ernie The Giant Chicken 0 read_csv(readr_example(\"chickens.csv\"), col_select = c(1, 3:4)) #> Rows: 5 Columns: 3 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (2): chicken, motto #> dbl (1): eggs_laid #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 3 #> chicken eggs_laid motto #> #> 1 Foghorn Leghorn 0 That's a joke, ah say, that's a joke,… #> 2 Chicken Little 3 The sky is falling! #> 3 Ginger 12 Listen. We'll either die free chicken… #> 4 Camilla the Chicken 7 Bawk, buck, ba-gawk. #> 5 Ernie The Giant Chicken 0 Put Captain Solo in the cargo hold. # Or use the selection helpers read_csv( readr_example(\"chickens.csv\"), col_select = c(starts_with(\"c\"), last_col()) ) #> Rows: 5 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (2): chicken, motto #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 2 #> chicken motto #> #> 1 Foghorn Leghorn That's a joke, ah say, that's a joke, son. #> 2 Chicken Little The sky is falling! #> 3 Ginger Listen. We'll either die free chickens or we di… #> 4 Camilla the Chicken Bawk, buck, ba-gawk. #> 5 Ernie The Giant Chicken Put Captain Solo in the cargo hold. # You can also rename specific columns read_csv( readr_example(\"chickens.csv\"), col_select = c(egg_yield = eggs_laid, everything()) ) #> Rows: 5 Columns: 4 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> chr (3): chicken, sex, motto #> dbl (1): eggs_laid #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 5 × 4 #> egg_yield chicken sex motto #> #> 1 0 Foghorn Leghorn rooster That's a joke, ah say, that's… #> 2 3 Chicken Little hen The sky is falling! #> 3 12 Ginger hen Listen. We'll either die free… #> 4 7 Camilla the Chicken hen Bawk, buck, ba-gawk. #> 5 0 Ernie The Giant Chicken rooster Put Captain Solo in the cargo… # Column types -------------------------------------------------------------- # By default, readr guesses the columns types, looking at `guess_max` rows. # You can override with a compact specification: read_csv(I(\"x,y\\n1,2\\n3,4\"), col_types = \"dc\") #> # A tibble: 2 × 2 #> x y #> #> 1 1 2 #> 2 3 4 # Or with a list of column types: read_csv(I(\"x,y\\n1,2\\n3,4\"), col_types = list(col_double(), col_character())) #> # A tibble: 2 × 2 #> x y #> #> 1 1 2 #> 2 3 4 # If there are parsing problems, you get a warning, and can extract # more details with problems() y <- read_csv(I(\"x\\n1\\n2\\nb\"), col_types = list(col_double())) #> Warning: One or more parsing issues, call `problems()` on your data frame for #> details, e.g.: #> dat <- vroom(...) #> problems(dat) y #> # A tibble: 3 × 1 #> x #> #> 1 1 #> 2 2 #> 3 NA problems(y) #> # A tibble: 1 × 5 #> row col expected actual file #> #> 1 4 1 a double b /tmp/RtmpmWxiqJ/file184720ad8f68 # Column names -------------------------------------------------------------- # By default, readr duplicate name repair is noisy read_csv(I(\"x,x\\n1,2\\n3,4\")) #> New names: #> • `x` -> `x...1` #> • `x` -> `x...2` #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x...1, x...2 #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x...1 x...2 #> #> 1 1 2 #> 2 3 4 # Same default repair strategy, but quiet read_csv(I(\"x,x\\n1,2\\n3,4\"), name_repair = \"unique_quiet\") #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x...1, x...2 #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x...1 x...2 #> #> 1 1 2 #> 2 3 4 # There's also a global option that controls verbosity of name repair withr::with_options( list(rlib_name_repair_verbosity = \"quiet\"), read_csv(I(\"x,x\\n1,2\\n3,4\")) ) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x...1, x...2 #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x...1 x...2 #> #> 1 1 2 #> 2 3 4 # Or use \"minimal\" to turn off name repair read_csv(I(\"x,x\\n1,2\\n3,4\"), name_repair = \"minimal\") #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): x, x #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> x x #> #> 1 1 2 #> 2 3 4 # File types ---------------------------------------------------------------- read_csv(I(\"a,b\\n1.0,2.0\")) #> Rows: 1 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (2): a, b #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 1 × 2 #> a b #> #> 1 1 2 read_csv2(I(\"a;b\\n1,0;2,0\")) #> ℹ Using \"','\" as decimal and \"'.'\" as grouping mark. Use `read_delim()` for more control. #> Rows: 1 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \";\" #> dbl (2): a, b #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 1 × 2 #> a b #> #> 1 1 2 read_tsv(I(\"a\\tb\\n1.0\\t2.0\")) #> Rows: 1 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \"\\t\" #> dbl (2): a, b #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 1 × 2 #> a b #> #> 1 1 2 read_delim(I(\"a|b\\n1.0|2.0\"), delim = \"|\") #> Rows: 1 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \"|\" #> dbl (2): a, b #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 1 × 2 #> a b #> #> 1 1 2"},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":null,"dir":"Reference","previous_headings":"","what":"Read a delimited file by chunks — read_delim_chunked","title":"Read a delimited file by chunks — read_delim_chunked","text":"Read delimited file chunks","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read a delimited file by chunks — read_delim_chunked","text":"","code":"read_delim_chunked( file, callback, delim = NULL, chunk_size = 10000, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, col_names = TRUE, col_types = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, guess_max = chunk_size, progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE ) read_csv_chunked( file, callback, chunk_size = 10000, col_names = TRUE, col_types = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, guess_max = chunk_size, progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE ) read_csv2_chunked( file, callback, chunk_size = 10000, col_names = TRUE, col_types = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, guess_max = chunk_size, progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE ) read_tsv_chunked( file, callback, chunk_size = 10000, col_names = TRUE, col_types = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, guess_max = chunk_size, progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read a delimited file by chunks — read_delim_chunked","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. callback callback function call chunk delim Single character used separate fields within record. chunk_size number rows include chunk quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read a delimited file by chunks — read_delim_chunked","text":"number lines file can exceed maximum integer value R (~2 billion).","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/read_delim_chunked.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read a delimited file by chunks — read_delim_chunked","text":"","code":"# Cars with 3 gears f <- function(x, pos) subset(x, gear == 3) read_csv_chunked(readr_example(\"mtcars.csv\"), DataFrameCallback$new(f), chunk_size = 5) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> # A tibble: 15 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 2 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 3 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 4 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 5 16.4 8 276. 180 3.07 4.07 17.4 0 0 3 3 #> 6 17.3 8 276. 180 3.07 3.73 17.6 0 0 3 3 #> 7 15.2 8 276. 180 3.07 3.78 18 0 0 3 3 #> 8 10.4 8 472 205 2.93 5.25 18.0 0 0 3 4 #> 9 10.4 8 460 215 3 5.42 17.8 0 0 3 4 #> 10 14.7 8 440 230 3.23 5.34 17.4 0 0 3 4 #> 11 21.5 4 120. 97 3.7 2.46 20.0 1 0 3 1 #> 12 15.5 8 318 150 2.76 3.52 16.9 0 0 3 2 #> 13 15.2 8 304 150 3.15 3.44 17.3 0 0 3 2 #> 14 13.3 8 350 245 3.73 3.84 15.4 0 0 3 4 #> 15 19.2 8 400 175 3.08 3.84 17.0 0 0 3 2"},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":null,"dir":"Reference","previous_headings":"","what":"Read/write a complete file — read_file","title":"Read/write a complete file — read_file","text":"read_file() reads complete file single object: either character vector length one, raw vector. write_file() takes single string, raw vector, writes exactly . Raw vectors useful dealing binary data, text data unknown encoding.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read/write a complete file — read_file","text":"","code":"read_file(file, locale = default_locale()) read_file_raw(file) write_file(x, file, append = FALSE, path = deprecated())"},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read/write a complete file — read_file","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. x single string, raw vector write disk. append FALSE, overwrite existing file. TRUE, append existing file. cases, file exist new file created. path Use file argument instead.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read/write a complete file — read_file","text":"read_file: length 1 character vector. read_lines_raw: raw vector.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_file.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read/write a complete file — read_file","text":"","code":"read_file(file.path(R.home(\"doc\"), \"AUTHORS\")) #> [1] \"Authors of R.\\n\\nR was initially written by Robert Gentleman and Ross Ihaka—also known as \\\"R & R\\\"\\nof the Statistics Department of the University of Auckland.\\n\\nSince mid-1997 there has been a core group with write access to the R\\nsource, currently consisting of\\n\\nDouglas Bates\\nJohn Chambers\\nPeter Dalgaard\\nRobert Gentleman\\nKurt Hornik\\nRoss Ihaka\\nTomas Kalibera\\nMichael Lawrence\\nFriedrich Leisch\\nUwe Ligges\\nThomas Lumley\\nMartin Maechler\\nSebastian Meyer\\nPaul Murrell\\nMartyn Plummer\\nBrian Ripley\\nDeepayan Sarkar\\nDuncan Temple Lang\\nLuke Tierney\\nSimon Urbanek\\n\\nplus Heiner Schwarte up to October 1999, Guido Masarotto up to June 2003,\\nStefano Iacus up to July 2014, Seth Falcon up to August 2015, Duncan Murdoch\\nup to September 2017, and Martin Morgan up to June 2021.\\n\\n\\nCurrent R-core members can be contacted via email to R-project.org\\nwith name made up by replacing spaces by dots in the name listed above.\\n\\n(The authors of code from other projects included in the R distribution\\nare listed in the COPYRIGHTS file.)\\n\" read_file_raw(file.path(R.home(\"doc\"), \"AUTHORS\")) #> [1] 41 75 74 68 6f 72 73 20 6f 66 20 52 2e 0a 0a 52 20 77 61 73 20 69 #> [23] 6e 69 74 69 61 6c 6c 79 20 77 72 69 74 74 65 6e 20 62 79 20 52 6f #> [45] 62 65 72 74 20 47 65 6e 74 6c 65 6d 61 6e 20 61 6e 64 20 52 6f 73 #> [67] 73 20 49 68 61 6b 61 e2 80 94 61 6c 73 6f 20 6b 6e 6f 77 6e 20 61 #> [89] 73 20 22 52 20 26 20 52 22 0a 6f 66 20 74 68 65 20 53 74 61 74 69 #> [111] 73 74 69 63 73 20 44 65 70 61 72 74 6d 65 6e 74 20 6f 66 20 74 68 #> [133] 65 20 55 6e 69 76 65 72 73 69 74 79 20 6f 66 20 41 75 63 6b 6c 61 #> [155] 6e 64 2e 0a 0a 53 69 6e 63 65 20 6d 69 64 2d 31 39 39 37 20 74 68 #> [177] 65 72 65 20 68 61 73 20 62 65 65 6e 20 61 20 63 6f 72 65 20 67 72 #> [199] 6f 75 70 20 77 69 74 68 20 77 72 69 74 65 20 61 63 63 65 73 73 20 #> [221] 74 6f 20 74 68 65 20 52 0a 73 6f 75 72 63 65 2c 20 63 75 72 72 65 #> [243] 6e 74 6c 79 20 63 6f 6e 73 69 73 74 69 6e 67 20 6f 66 0a 0a 44 6f #> [265] 75 67 6c 61 73 20 42 61 74 65 73 0a 4a 6f 68 6e 20 43 68 61 6d 62 #> [287] 65 72 73 0a 50 65 74 65 72 20 44 61 6c 67 61 61 72 64 0a 52 6f 62 #> [309] 65 72 74 20 47 65 6e 74 6c 65 6d 61 6e 0a 4b 75 72 74 20 48 6f 72 #> [331] 6e 69 6b 0a 52 6f 73 73 20 49 68 61 6b 61 0a 54 6f 6d 61 73 20 4b #> [353] 61 6c 69 62 65 72 61 0a 4d 69 63 68 61 65 6c 20 4c 61 77 72 65 6e #> [375] 63 65 0a 46 72 69 65 64 72 69 63 68 20 4c 65 69 73 63 68 0a 55 77 #> [397] 65 20 4c 69 67 67 65 73 0a 54 68 6f 6d 61 73 20 4c 75 6d 6c 65 79 #> [419] 0a 4d 61 72 74 69 6e 20 4d 61 65 63 68 6c 65 72 0a 53 65 62 61 73 #> [441] 74 69 61 6e 20 4d 65 79 65 72 0a 50 61 75 6c 20 4d 75 72 72 65 6c #> [463] 6c 0a 4d 61 72 74 79 6e 20 50 6c 75 6d 6d 65 72 0a 42 72 69 61 6e #> [485] 20 52 69 70 6c 65 79 0a 44 65 65 70 61 79 61 6e 20 53 61 72 6b 61 #> [507] 72 0a 44 75 6e 63 61 6e 20 54 65 6d 70 6c 65 20 4c 61 6e 67 0a 4c #> [529] 75 6b 65 20 54 69 65 72 6e 65 79 0a 53 69 6d 6f 6e 20 55 72 62 61 #> [551] 6e 65 6b 0a 0a 70 6c 75 73 20 48 65 69 6e 65 72 20 53 63 68 77 61 #> [573] 72 74 65 20 75 70 20 74 6f 20 4f 63 74 6f 62 65 72 20 31 39 39 39 #> [595] 2c 20 47 75 69 64 6f 20 4d 61 73 61 72 6f 74 74 6f 20 75 70 20 74 #> [617] 6f 20 4a 75 6e 65 20 32 30 30 33 2c 0a 53 74 65 66 61 6e 6f 20 49 #> [639] 61 63 75 73 20 75 70 20 74 6f 20 4a 75 6c 79 20 32 30 31 34 2c 20 #> [661] 53 65 74 68 20 46 61 6c 63 6f 6e 20 75 70 20 74 6f 20 41 75 67 75 #> [683] 73 74 20 32 30 31 35 2c 20 44 75 6e 63 61 6e 20 4d 75 72 64 6f 63 #> [705] 68 0a 75 70 20 74 6f 20 53 65 70 74 65 6d 62 65 72 20 32 30 31 37 #> [727] 2c 20 61 6e 64 20 4d 61 72 74 69 6e 20 4d 6f 72 67 61 6e 20 75 70 #> [749] 20 74 6f 20 4a 75 6e 65 20 32 30 32 31 2e 0a 0a 0a 43 75 72 72 65 #> [771] 6e 74 20 52 2d 63 6f 72 65 20 6d 65 6d 62 65 72 73 20 63 61 6e 20 #> [793] 62 65 20 63 6f 6e 74 61 63 74 65 64 20 76 69 61 20 65 6d 61 69 6c #> [815] 20 74 6f 20 52 2d 70 72 6f 6a 65 63 74 2e 6f 72 67 0a 77 69 74 68 #> [837] 20 6e 61 6d 65 20 6d 61 64 65 20 75 70 20 62 79 20 72 65 70 6c 61 #> [859] 63 69 6e 67 20 73 70 61 63 65 73 20 62 79 20 64 6f 74 73 20 69 6e #> [881] 20 74 68 65 20 6e 61 6d 65 20 6c 69 73 74 65 64 20 61 62 6f 76 65 #> [903] 2e 0a 0a 28 54 68 65 20 61 75 74 68 6f 72 73 20 6f 66 20 63 6f 64 #> [925] 65 20 66 72 6f 6d 20 6f 74 68 65 72 20 70 72 6f 6a 65 63 74 73 20 #> [947] 69 6e 63 6c 75 64 65 64 20 69 6e 20 74 68 65 20 52 20 64 69 73 74 #> [969] 72 69 62 75 74 69 6f 6e 0a 61 72 65 20 6c 69 73 74 65 64 20 69 6e #> [991] 20 74 68 65 20 43 4f 50 59 52 49 47 48 54 53 20 66 69 6c 65 2e 29 #> [1013] 0a tmp <- tempfile() x <- format_csv(mtcars[1:6, ]) write_file(x, tmp) identical(x, read_file(tmp)) #> [1] TRUE read_lines(I(x)) #> [1] \"mpg,cyl,disp,hp,drat,wt,qsec,vs,am,gear,carb\" #> [2] \"21,6,160,110,3.9,2.62,16.46,0,1,4,4\" #> [3] \"21,6,160,110,3.9,2.875,17.02,0,1,4,4\" #> [4] \"22.8,4,108,93,3.85,2.32,18.61,1,1,4,1\" #> [5] \"21.4,6,258,110,3.08,3.215,19.44,1,0,3,1\" #> [6] \"18.7,8,360,175,3.15,3.44,17.02,0,0,3,2\" #> [7] \"18.1,6,225,105,2.76,3.46,20.22,1,0,3,1\""},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":null,"dir":"Reference","previous_headings":"","what":"Read a fixed width file into a tibble — read_fwf","title":"Read a fixed width file into a tibble — read_fwf","text":"fixed width file can compact representation numeric data. also fast parse, every field place every line. Unfortunately, painful parse need describe length every field. Readr aims make easy possible providing number different ways describe field structure. fwf_empty() - Guesses based positions empty columns. fwf_widths() - Supply widths columns. fwf_positions() - Supply paired vectors start end positions. fwf_cols() - Supply named arguments paired start end positions column widths.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read a fixed width file into a tibble — read_fwf","text":"","code":"read_fwf( file, col_positions = fwf_empty(file, skip, n = guess_max), col_types = NULL, col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), comment = \"\", trim_ws = TRUE, skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), lazy = should_read_lazy(), skip_empty_rows = TRUE ) fwf_empty( file, skip = 0, skip_empty_rows = FALSE, col_names = NULL, comment = \"\", n = 100L ) fwf_widths(widths, col_names = NULL) fwf_positions(start, end = NULL, col_names = NULL) fwf_cols(...)"},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read a fixed width file into a tibble — read_fwf","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. col_positions Column positions, created fwf_empty(), fwf_widths() fwf_positions(). read selected fields, use fwf_positions(). width last column variable (ragged fwf file), supply last end position NA. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). col_select Columns include results. can use mini-language dplyr::select() refer columns name. Use c() use one selection expression. Although usage less common, col_select also accepts numeric column index. See ?tidyselect::language full details selection language. id name column store file path. useful reading multiple input files data file paths, data collection date. NULL (default) extra column created. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. name_repair Handling column names. default behaviour ensure column names \"unique\". Various repair strategies supported: \"minimal\": name repair checks, beyond basic existence names. \"unique\" (default value): Make sure names unique empty. \"check_unique\": name repair, check unique. \"unique_quiet\": Repair unique strategy, quietly. \"universal\": Make names unique syntactic. \"universal_quiet\": Repair universal strategy, quietly. function: Apply custom name repair (e.g., name_repair = make.names names style base R). purrr-style anonymous function, see rlang::as_function(). argument passed repair vctrs::vec_as_names(). See details terms strategies used enforce . num_threads number processing threads use initial parsing lazy reading data. data contains newlines within fields parser automatically detect fall back using one thread . However know file newlines within quoted fields safest set num_threads = 1 explicitly. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. lazy Read values lazily? default, FALSE, special considerations reading file lazily tripped users. Specifically, things get tricky reading writing back file. , general, lazy reading (lazy = TRUE) many benefits, especially interactive use downstream work involves subset rows columns. Learn should_read_lazy() documentation altrep argument vroom::vroom(). skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. col_names Either NULL, character vector column names. n Number lines tokenizer read determine file structure. default set 100. widths Width field. Use NA width last field reading ragged fwf file. start, end Starting ending (inclusive) positions field. Use NA last end field reading ragged fwf file. ... first element data frame, must numeric columns either one two rows. column names variable names. column values variable widths length one vector, length two, variable start end positions. elements ... used construct data frame two rows .","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":"second-edition-changes","dir":"Reference","previous_headings":"","what":"Second edition changes","title":"Read a fixed width file into a tibble — read_fwf","text":"Comments longer looked anywhere file. now ignored start line.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/read_fwf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read a fixed width file into a tibble — read_fwf","text":"","code":"fwf_sample <- readr_example(\"fwf-sample.txt\") writeLines(read_lines(fwf_sample)) #> John Smith WA 418-Y11-4111 #> Mary Hartford CA 319-Z19-4341 #> Evan Nolan IL 219-532-c301 # You can specify column positions in several ways: # 1. Guess based on position of empty columns read_fwf(fwf_sample, fwf_empty(fwf_sample, col_names = c(\"first\", \"last\", \"state\", \"ssn\"))) #> Rows: 3 Columns: 4 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (4): first, last, state, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 4 #> first last state ssn #> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301 # 2. A vector of field widths read_fwf(fwf_sample, fwf_widths(c(20, 10, 12), c(\"name\", \"state\", \"ssn\"))) #> Rows: 3 Columns: 3 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (3): name, state, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 3 #> name state ssn #> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301 # 3. Paired vectors of start and end positions read_fwf(fwf_sample, fwf_positions(c(1, 30), c(20, 42), c(\"name\", \"ssn\"))) #> Rows: 3 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (2): name, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 2 #> name ssn #> #> 1 John Smith 418-Y11-4111 #> 2 Mary Hartford 319-Z19-4341 #> 3 Evan Nolan 219-532-c301 # 4. Named arguments with start and end positions read_fwf(fwf_sample, fwf_cols(name = c(1, 20), ssn = c(30, 42))) #> Rows: 3 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (2): name, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 2 #> name ssn #> #> 1 John Smith 418-Y11-4111 #> 2 Mary Hartford 319-Z19-4341 #> 3 Evan Nolan 219-532-c301 # 5. Named arguments with column widths read_fwf(fwf_sample, fwf_cols(name = 20, state = 10, ssn = 12)) #> Rows: 3 Columns: 3 #> ── Column specification ────────────────────────────────────────────────── #> #> chr (3): name, state, ssn #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 3 × 3 #> name state ssn #> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301"},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":null,"dir":"Reference","previous_headings":"","what":"Read/write lines to/from a file — read_lines","title":"Read/write lines to/from a file — read_lines","text":"read_lines() reads n_max lines file. New lines included output. read_lines_raw() produces list raw vectors, useful handling data unknown encoding. write_lines() takes character vector list raw vectors, appending new line entry.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read/write lines to/from a file — read_lines","text":"","code":"read_lines( file, skip = 0, skip_empty_rows = FALSE, n_max = Inf, locale = default_locale(), na = character(), lazy = should_read_lazy(), num_threads = readr_threads(), progress = show_progress() ) read_lines_raw( file, skip = 0, n_max = -1L, num_threads = readr_threads(), progress = show_progress() ) write_lines( x, file, sep = \"\\n\", na = \"NA\", append = FALSE, num_threads = readr_threads(), path = deprecated() )"},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read/write lines to/from a file — read_lines","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. skip Number lines skip reading data. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. n_max Number lines read. n_max -1, lines file read. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. lazy Read values lazily? default, FALSE, special considerations reading file lazily tripped users. Specifically, things get tricky reading writing back file. , general, lazy reading (lazy = TRUE) many benefits, especially interactive use downstream work involves subset rows columns. Learn should_read_lazy() documentation altrep argument vroom::vroom(). num_threads number processing threads use initial parsing lazy reading data. data contains newlines within fields parser automatically detect fall back using one thread . However know file newlines within quoted fields safest set num_threads = 1 explicitly. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. x character vector list raw vectors write disk. sep line separator. Defaults \\\\n, commonly used POSIX systems like macOS linux. native windows (CRLF) separators use \\\\r\\\\n. append FALSE, overwrite existing file. TRUE, append existing file. cases, file exist new file created. path Use file argument instead.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read/write lines to/from a file — read_lines","text":"read_lines(): character vector one element line. read_lines_raw(): list containing raw vector line. write_lines() returns x, invisibly.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read/write lines to/from a file — read_lines","text":"","code":"read_lines(file.path(R.home(\"doc\"), \"AUTHORS\"), n_max = 10) #> [1] \"Authors of R.\" #> [2] \"\" #> [3] \"R was initially written by Robert Gentleman and Ross Ihaka—also known as \\\"R & R\\\"\" #> [4] \"of the Statistics Department of the University of Auckland.\" #> [5] \"\" #> [6] \"Since mid-1997 there has been a core group with write access to the R\" #> [7] \"source, currently consisting of\" #> [8] \"\" #> [9] \"Douglas Bates\" #> [10] \"John Chambers\" read_lines_raw(file.path(R.home(\"doc\"), \"AUTHORS\"), n_max = 10) #> [[1]] #> [1] 41 75 74 68 6f 72 73 20 6f 66 20 52 2e #> #> [[2]] #> raw(0) #> #> [[3]] #> [1] 52 20 77 61 73 20 69 6e 69 74 69 61 6c 6c 79 20 77 72 69 74 74 65 6e #> [24] 20 62 79 20 52 6f 62 65 72 74 20 47 65 6e 74 6c 65 6d 61 6e 20 61 6e #> [47] 64 20 52 6f 73 73 20 49 68 61 6b 61 e2 80 94 61 6c 73 6f 20 6b 6e 6f #> [70] 77 6e 20 61 73 20 22 52 20 26 20 52 22 #> #> [[4]] #> [1] 6f 66 20 74 68 65 20 53 74 61 74 69 73 74 69 63 73 20 44 65 70 61 72 #> [24] 74 6d 65 6e 74 20 6f 66 20 74 68 65 20 55 6e 69 76 65 72 73 69 74 79 #> [47] 20 6f 66 20 41 75 63 6b 6c 61 6e 64 2e #> #> [[5]] #> raw(0) #> #> [[6]] #> [1] 53 69 6e 63 65 20 6d 69 64 2d 31 39 39 37 20 74 68 65 72 65 20 68 61 #> [24] 73 20 62 65 65 6e 20 61 20 63 6f 72 65 20 67 72 6f 75 70 20 77 69 74 #> [47] 68 20 77 72 69 74 65 20 61 63 63 65 73 73 20 74 6f 20 74 68 65 20 52 #> #> [[7]] #> [1] 73 6f 75 72 63 65 2c 20 63 75 72 72 65 6e 74 6c 79 20 63 6f 6e 73 69 #> [24] 73 74 69 6e 67 20 6f 66 #> #> [[8]] #> raw(0) #> #> [[9]] #> [1] 44 6f 75 67 6c 61 73 20 42 61 74 65 73 #> #> [[10]] #> [1] 4a 6f 68 6e 20 43 68 61 6d 62 65 72 73 #> tmp <- tempfile() write_lines(rownames(mtcars), tmp) read_lines(tmp, lazy = FALSE) #> [1] \"Mazda RX4\" \"Mazda RX4 Wag\" \"Datsun 710\" #> [4] \"Hornet 4 Drive\" \"Hornet Sportabout\" \"Valiant\" #> [7] \"Duster 360\" \"Merc 240D\" \"Merc 230\" #> [10] \"Merc 280\" \"Merc 280C\" \"Merc 450SE\" #> [13] \"Merc 450SL\" \"Merc 450SLC\" \"Cadillac Fleetwood\" #> [16] \"Lincoln Continental\" \"Chrysler Imperial\" \"Fiat 128\" #> [19] \"Honda Civic\" \"Toyota Corolla\" \"Toyota Corona\" #> [22] \"Dodge Challenger\" \"AMC Javelin\" \"Camaro Z28\" #> [25] \"Pontiac Firebird\" \"Fiat X1-9\" \"Porsche 914-2\" #> [28] \"Lotus Europa\" \"Ford Pantera L\" \"Ferrari Dino\" #> [31] \"Maserati Bora\" \"Volvo 142E\" read_file(tmp) # note trailing \\n #> [1] \"Mazda RX4\\nMazda RX4 Wag\\nDatsun 710\\nHornet 4 Drive\\nHornet Sportabout\\nValiant\\nDuster 360\\nMerc 240D\\nMerc 230\\nMerc 280\\nMerc 280C\\nMerc 450SE\\nMerc 450SL\\nMerc 450SLC\\nCadillac Fleetwood\\nLincoln Continental\\nChrysler Imperial\\nFiat 128\\nHonda Civic\\nToyota Corolla\\nToyota Corona\\nDodge Challenger\\nAMC Javelin\\nCamaro Z28\\nPontiac Firebird\\nFiat X1-9\\nPorsche 914-2\\nLotus Europa\\nFord Pantera L\\nFerrari Dino\\nMaserati Bora\\nVolvo 142E\\n\" write_lines(airquality$Ozone, tmp, na = \"-1\") read_lines(tmp) #> [1] \"41\" \"36\" \"12\" \"18\" \"-1\" \"28\" \"23\" \"19\" \"8\" \"-1\" \"7\" #> [12] \"16\" \"11\" \"14\" \"18\" \"14\" \"34\" \"6\" \"30\" \"11\" \"1\" \"11\" #> [23] \"4\" \"32\" \"-1\" \"-1\" \"-1\" \"23\" \"45\" \"115\" \"37\" \"-1\" \"-1\" #> [34] \"-1\" \"-1\" \"-1\" \"-1\" \"29\" \"-1\" \"71\" \"39\" \"-1\" \"-1\" \"23\" #> [45] \"-1\" \"-1\" \"21\" \"37\" \"20\" \"12\" \"13\" \"-1\" \"-1\" \"-1\" \"-1\" #> [56] \"-1\" \"-1\" \"-1\" \"-1\" \"-1\" \"-1\" \"135\" \"49\" \"32\" \"-1\" \"64\" #> [67] \"40\" \"77\" \"97\" \"97\" \"85\" \"-1\" \"10\" \"27\" \"-1\" \"7\" \"48\" #> [78] \"35\" \"61\" \"79\" \"63\" \"16\" \"-1\" \"-1\" \"80\" \"108\" \"20\" \"52\" #> [89] \"82\" \"50\" \"64\" \"59\" \"39\" \"9\" \"16\" \"78\" \"35\" \"66\" \"122\" #> [100] \"89\" \"110\" \"-1\" \"-1\" \"44\" \"28\" \"65\" \"-1\" \"22\" \"59\" \"23\" #> [111] \"31\" \"44\" \"21\" \"9\" \"-1\" \"45\" \"168\" \"73\" \"-1\" \"76\" \"118\" #> [122] \"84\" \"85\" \"96\" \"78\" \"73\" \"91\" \"47\" \"32\" \"20\" \"23\" \"21\" #> [133] \"24\" \"44\" \"21\" \"28\" \"9\" \"13\" \"46\" \"18\" \"13\" \"24\" \"16\" #> [144] \"13\" \"23\" \"36\" \"7\" \"14\" \"30\" \"-1\" \"14\" \"18\" \"20\""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines_chunked.html","id":null,"dir":"Reference","previous_headings":"","what":"Read lines from a file or string by chunk. — read_lines_chunked","title":"Read lines from a file or string by chunk. — read_lines_chunked","text":"Read lines file string chunk.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_lines_chunked.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read lines from a file or string by chunk. — read_lines_chunked","text":"","code":"read_lines_chunked( file, callback, chunk_size = 10000, skip = 0, locale = default_locale(), na = character(), progress = show_progress() ) read_lines_raw_chunked( file, callback, chunk_size = 10000, skip = 0, progress = show_progress() )"},{"path":"https://readr.tidyverse.org/dev/reference/read_lines_chunked.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read lines from a file or string by chunk. — read_lines_chunked","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. callback callback function call chunk chunk_size number rows include chunk skip Number lines skip reading data. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/read_log.html","id":null,"dir":"Reference","previous_headings":"","what":"Read common/combined log file into a tibble — read_log","title":"Read common/combined log file into a tibble — read_log","text":"fairly standard format log files - uses quotes square brackets quoting, may literal quotes embedded quoted string. dash, \"-\", used missing values.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_log.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read common/combined log file into a tibble — read_log","text":"","code":"read_log( file, col_names = FALSE, col_types = NULL, trim_ws = TRUE, skip = 0, n_max = Inf, show_col_types = should_show_types(), progress = show_progress() )"},{"path":"https://readr.tidyverse.org/dev/reference/read_log.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read common/combined log file into a tibble — read_log","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. n_max Maximum number lines read. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_log.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read common/combined log file into a tibble — read_log","text":"","code":"read_log(readr_example(\"example.log\")) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> X1 = col_character(), #> X2 = col_logical(), #> X3 = col_character(), #> X4 = col_character(), #> X5 = col_character(), #> X6 = col_double(), #> X7 = col_double() #> ) #> # A tibble: 2 × 7 #> X1 X2 X3 X4 X5 X6 X7 #> #> 1 172.21.13.45 NA \"Microsoft\\\\JohnDoe\" 08/Apr/2001:1… GET … 200 3401 #> 2 127.0.0.1 NA \"frank\" 10/Oct/2000:1… GET … 200 2326"},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":null,"dir":"Reference","previous_headings":"","what":"Read/write RDS files. — read_rds","title":"Read/write RDS files. — read_rds","text":"Consistent wrapper around saveRDS() readRDS(). write_rds() compress default space generally cheaper time.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read/write RDS files. — read_rds","text":"","code":"read_rds(file, refhook = NULL) write_rds( x, file, compress = c(\"none\", \"gz\", \"bz2\", \"xz\"), version = 2, refhook = NULL, text = FALSE, path = deprecated(), ... )"},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read/write RDS files. — read_rds","text":"file file path read /write . refhook function handle reference objects. x R object write serialise. compress Compression method use: \"none\", \"gz\" ,\"bz\", \"xz\". version Serialization format version used. default value 2 compatible R versions prior 3.5.0. See base::saveRDS() details. text TRUE text representation used, otherwise binary representation used. path Use file argument instead. ... Additional arguments connection function. example, control space-time trade-different compression methods compression. See connections() details.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read/write RDS files. — read_rds","text":"write_rds() returns x, invisibly.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_rds.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read/write RDS files. — read_rds","text":"","code":"temp <- tempfile() write_rds(mtcars, temp) read_rds(temp) #> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 if (FALSE) { write_rds(mtcars, \"compressed_mtc.rds\", \"xz\", compression = 9L) }"},{"path":"https://readr.tidyverse.org/dev/reference/read_table.html","id":null,"dir":"Reference","previous_headings":"","what":"Read whitespace-separated columns into a tibble — read_table","title":"Read whitespace-separated columns into a tibble — read_table","text":"read_table() designed read type textual data column separated one () columns space. read_table() like read.table(), allows number whitespace characters columns, lines can different lengths. spec_table() returns column specifications rather data frame.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_table.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read whitespace-separated columns into a tibble — read_table","text":"","code":"read_table( file, col_names = TRUE, col_types = NULL, locale = default_locale(), na = \"NA\", skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress(), comment = \"\", show_col_types = should_show_types(), skip_empty_rows = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/read_table.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read whitespace-separated columns into a tibble — read_table","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. skip Number lines skip reading data. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. comment string used identify comments. text comment characters silently ignored. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/read_table.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read whitespace-separated columns into a tibble — read_table","text":"","code":"ws <- readr_example(\"whitespace-sample.txt\") writeLines(read_lines(ws)) #> first last state phone #> John Smith WA 418-Y11-4111 #> Mary Hartford CA 319-Z19-4341 #> Evan Nolan IL 219-532-c301 read_table(ws) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> first = col_character(), #> last = col_character(), #> state = col_character(), #> phone = col_character() #> ) #> # A tibble: 3 × 4 #> first last state phone #> #> 1 John Smith WA 418-Y11-4111 #> 2 Mary Hartford CA 319-Z19-4341 #> 3 Evan Nolan IL 219-532-c301"},{"path":"https://readr.tidyverse.org/dev/reference/read_table2.html","id":null,"dir":"Reference","previous_headings":"","what":"Read whitespace-separated columns into a tibble — read_table2","title":"Read whitespace-separated columns into a tibble — read_table2","text":"function deprecated renamed read_table() removed old read_table function, strict cases analogous just using read_fwf().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/read_table2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read whitespace-separated columns into a tibble — read_table2","text":"","code":"read_table2( file, col_names = TRUE, col_types = NULL, locale = default_locale(), na = \"NA\", skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = show_progress(), comment = \"\", skip_empty_rows = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/readr-package.html","id":null,"dir":"Reference","previous_headings":"","what":"readr: Read Rectangular Text Data — readr-package","title":"readr: Read Rectangular Text Data — readr-package","text":"goal 'readr' provide fast friendly way read rectangular data (like 'csv', 'tsv', 'fwf'). designed flexibly parse many types data found wild, still cleanly failing data unexpectedly changes.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/readr-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"readr: Read Rectangular Text Data — readr-package","text":"Maintainer: Jennifer Bryan jenny@posit.co (ORCID) Authors: Hadley Wickham hadley@posit.co Jim Hester contributors: Romain Francois [contributor] Shelby Bearrows [contributor] Posit Software, PBC [copyright holder, funder] https://github.com/mandreyel/ (mio library) [copyright holder] Jukka Jylänki (grisu3 implementation) [contributor, copyright holder] Mikkel Jørgensen (grisu3 implementation) [contributor, copyright holder]","code":""},{"path":"https://readr.tidyverse.org/dev/reference/readr_example.html","id":null,"dir":"Reference","previous_headings":"","what":"Get path to readr example — readr_example","title":"Get path to readr example — readr_example","text":"readr comes bundled number sample files inst/extdata directory. function make easy access","code":""},{"path":"https://readr.tidyverse.org/dev/reference/readr_example.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get path to readr example — readr_example","text":"","code":"readr_example(file = NULL)"},{"path":"https://readr.tidyverse.org/dev/reference/readr_example.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get path to readr example — readr_example","text":"file Name file. NULL, example files listed.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/readr_example.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get path to readr example — readr_example","text":"","code":"readr_example() #> [1] \"challenge.csv\" \"chickens.csv\" #> [3] \"epa78.txt\" \"example.log\" #> [5] \"fwf-sample.txt\" \"massey-rating.txt\" #> [7] \"mini-gapminder-africa.csv\" \"mini-gapminder-americas.csv\" #> [9] \"mini-gapminder-asia.csv\" \"mini-gapminder-europe.csv\" #> [11] \"mini-gapminder-oceania.csv\" \"mtcars.csv\" #> [13] \"mtcars.csv.bz2\" \"mtcars.csv.zip\" #> [15] \"whitespace-sample.txt\" readr_example(\"challenge.csv\") #> [1] \"/home/runner/work/_temp/Library/readr/extdata/challenge.csv\""},{"path":"https://readr.tidyverse.org/dev/reference/readr_threads.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine how many threads readr should use when processing — readr_threads","title":"Determine how many threads readr should use when processing — readr_threads","text":"number threads returned can set global option readr.num_threads environment variable VROOM_THREADS value parallel::detectCores()","code":""},{"path":"https://readr.tidyverse.org/dev/reference/readr_threads.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine how many threads readr should use when processing — readr_threads","text":"","code":"readr_threads()"},{"path":"https://readr.tidyverse.org/dev/reference/should_read_lazy.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine whether to read a file lazily — should_read_lazy","title":"Determine whether to read a file lazily — should_read_lazy","text":"function consults option readr.read_lazy figure whether lazy reading . option unset, default FALSE, meaning readr read files eagerly, lazily. want use option express preference lazy reading, : Typically, one use option control lazy reading session, file, user level. lazy argument functions like read_csv() can used control laziness individual call.","code":"options(readr.read_lazy = TRUE)"},{"path":"https://readr.tidyverse.org/dev/reference/should_read_lazy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine whether to read a file lazily — should_read_lazy","text":"","code":"should_read_lazy()"},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/should_show_types.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine whether column types should be shown — should_show_types","title":"Determine whether column types should be shown — should_show_types","text":"Wrapper around getOption(\"readr.show_col_types\") implements fall back logic option unset. returns: TRUE option set TRUE FALSE option set FALSE FALSE option unset appear running tests NULL otherwise, case caller determines whether show column types based context, e.g. whether show_col_types actual col_types explicitly specified","code":""},{"path":"https://readr.tidyverse.org/dev/reference/should_show_types.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine whether column types should be shown — should_show_types","text":"","code":"should_show_types()"},{"path":"https://readr.tidyverse.org/dev/reference/show_progress.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine whether progress bars should be shown — show_progress","title":"Determine whether progress bars should be shown — show_progress","text":"default, readr shows progress bars. However, progress reporting suppressed following conditions hold: bar explicitly disabled setting options(readr.show_progress = FALSE). code run non-interactive session, determined rlang::is_interactive(). code run RStudio notebook chunk, determined getOption(\"rstudio.notebook.executing\").","code":""},{"path":"https://readr.tidyverse.org/dev/reference/show_progress.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine whether progress bars should be shown — show_progress","text":"","code":"show_progress()"},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":null,"dir":"Reference","previous_headings":"","what":"Examine the column specifications for a data frame — cols_condense","title":"Examine the column specifications for a data frame — cols_condense","text":"cols_condense() takes spec object condenses definition setting default column type frequent type listing columns different type. spec() extracts full column specification tibble created readr.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Examine the column specifications for a data frame — cols_condense","text":"","code":"cols_condense(x) spec(x)"},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Examine the column specifications for a data frame — cols_condense","text":"x data frame object extract ","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Examine the column specifications for a data frame — cols_condense","text":"col_spec object.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/reference/spec.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Examine the column specifications for a data frame — cols_condense","text":"","code":"df <- read_csv(readr_example(\"mtcars.csv\")) #> Rows: 32 Columns: 11 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. s <- spec(df) s #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) cols_condense(s) #> cols( #> .default = col_double() #> )"},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a column specification — spec_delim","title":"Generate a column specification — spec_delim","text":"printed, first 20 columns printed default. override, set options(readr.num_columns) can used modify (value 0 turns printing).","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a column specification — spec_delim","text":"","code":"spec_delim( file, delim = NULL, quote = \"\\\"\", escape_backslash = FALSE, escape_double = TRUE, col_names = TRUE, col_types = list(), col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, comment = \"\", trim_ws = FALSE, skip = 0, n_max = 0, guess_max = 1000, name_repair = \"unique\", num_threads = readr_threads(), progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) spec_csv( file, col_names = TRUE, col_types = list(), col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = 0, guess_max = 1000, name_repair = \"unique\", num_threads = readr_threads(), progress = show_progress(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) spec_csv2( file, col_names = TRUE, col_types = list(), col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = 0, guess_max = 1000, progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) spec_tsv( file, col_names = TRUE, col_types = list(), col_select = NULL, id = NULL, locale = default_locale(), na = c(\"\", \"NA\"), quoted_na = TRUE, quote = \"\\\"\", comment = \"\", trim_ws = TRUE, skip = 0, n_max = 0, guess_max = 1000, progress = show_progress(), name_repair = \"unique\", num_threads = readr_threads(), show_col_types = should_show_types(), skip_empty_rows = TRUE, lazy = should_read_lazy() ) spec_table( file, col_names = TRUE, col_types = list(), locale = default_locale(), na = \"NA\", skip = 0, n_max = 0, guess_max = 1000, progress = show_progress(), comment = \"\", show_col_types = should_show_types(), skip_empty_rows = TRUE )"},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a column specification — spec_delim","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. delim Single character used separate fields within record. quote Single character used quote strings. escape_backslash file use backslashes escape special characters? general escape_double backslashes can used escape delimiter character, quote character, add special characters like \\\\n. escape_double file escape quotes doubling ? .e. option TRUE, value \"\"\"\" represents single quote, \\\". col_names Either TRUE, FALSE character vector column names. TRUE, first row input used column names, included data frame. FALSE, column names generated automatically: X1, X2, X3 etc. col_names character vector, values used names columns, first row input read first row output data frame. Missing (NA) column names generate warning, filled dummy names ...1, ...2 etc. Duplicate column names generate warning made unique, see name_repair control done. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types inferred guess_max rows input, interspersed throughout file. convenient (fast), robust. guessed types wrong, need increase guess_max supply correct types . Column specifications created list() cols() must contain one column specification column. want read subset columns, use cols_only(). Alternatively, can use compact string representation character represents one column: c = character = integer n = number d = double l = logical f = factor D = date T = date time t = time ? = guess _ - = skip default, reading file without column specification print message showing readr guessed . remove message, set show_col_types = FALSE set options(readr.show_col_types = FALSE). col_select Columns include results. can use mini-language dplyr::select() refer columns name. Use c() use one selection expression. Although usage less common, col_select also accepts numeric column index. See ?tidyselect::language full details selection language. id name column store file path. useful reading multiple input files data file paths, data collection date. NULL (default) extra column created. locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. na Character vector strings interpret missing values. Set option character() indicate missing values. quoted_na missing values inside quotes treated missing values (default) strings. parameter soft deprecated readr 2.0.0. comment string used identify comments. text comment characters silently ignored. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? skip Number lines skip reading data. comment supplied commented lines ignored skipping. n_max Maximum number lines read. guess_max Maximum number lines use guessing column types. never use number lines read. See vignette(\"column-types\", package = \"readr\") details. name_repair Handling column names. default behaviour ensure column names \"unique\". Various repair strategies supported: \"minimal\": name repair checks, beyond basic existence names. \"unique\" (default value): Make sure names unique empty. \"check_unique\": name repair, check unique. \"unique_quiet\": Repair unique strategy, quietly. \"universal\": Make names unique syntactic. \"universal_quiet\": Repair universal strategy, quietly. function: Apply custom name repair (e.g., name_repair = make.names names style base R). purrr-style anonymous function, see rlang::as_function(). argument passed repair vctrs::vec_as_names(). See details terms strategies used enforce . num_threads number processing threads use initial parsing lazy reading data. data contains newlines within fields parser automatically detect fall back using one thread . However know file newlines within quoted fields safest set num_threads = 1 explicitly. progress Display progress bar? default display interactive session knitting document. automatic progress bar can disabled setting option readr.show_progress FALSE. show_col_types FALSE, show guessed column types. TRUE always show column types, even supplied. NULL (default) show column types explicitly supplied col_types argument. skip_empty_rows blank rows ignored altogether? .e. option TRUE blank rows represented . FALSE represented NA values columns. lazy Read values lazily? default, FALSE, special considerations reading file lazily tripped users. Specifically, things get tricky reading writing back file. , general, lazy reading (lazy = TRUE) many benefits, especially interactive use downstream work involves subset rows columns. Learn should_read_lazy() documentation altrep argument vroom::vroom().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a column specification — spec_delim","text":"col_spec generated file.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/spec_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a column specification — spec_delim","text":"","code":"# Input sources ------------------------------------------------------------- # Retrieve specs from a path spec_csv(system.file(\"extdata/mtcars.csv\", package = \"readr\")) #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) spec_csv(system.file(\"extdata/mtcars.csv.zip\", package = \"readr\")) #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) # Or directly from a string (must contain a newline) spec_csv(I(\"x,y\\n1,2\\n3,4\")) #> cols( #> x = col_double(), #> y = col_double() #> ) # Column types -------------------------------------------------------------- # By default, readr guesses the columns types, looking at 1000 rows # throughout the file. # You can specify the number of rows used with guess_max. spec_csv(system.file(\"extdata/mtcars.csv\", package = \"readr\"), guess_max = 20) #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> )"},{"path":"https://readr.tidyverse.org/dev/reference/tokenize.html","id":null,"dir":"Reference","previous_headings":"","what":"Tokenize a file/string. — tokenize","title":"Tokenize a file/string. — tokenize","text":"Turns input character vector. Usually tokenization done purely C++, never exposed R (requires copy). function useful testing, file parse correctly want see underlying tokens.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/tokenize.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tokenize a file/string. — tokenize","text":"","code":"tokenize(file, tokenizer = tokenizer_csv(), skip = 0, n_max = -1L)"},{"path":"https://readr.tidyverse.org/dev/reference/tokenize.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tokenize a file/string. — tokenize","text":"file Either path file, connection, literal data (either single string raw vector). Files ending .gz, .bz2, .xz, .zip automatically uncompressed. Files starting http://, https://, ftp://, ftps:// automatically downloaded. Remote gz files can also automatically downloaded decompressed. Literal data useful examples tests. recognised literal data, input must either wrapped (), string containing least one new line, vector containing least one string new line. Using value clipboard() read system clipboard. tokenizer tokenizer specification. skip Number lines skip reading data. n_max Optionally, maximum number rows tokenize.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/tokenize.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Tokenize a file/string. — tokenize","text":"","code":"tokenize(\"1,2\\n3,4,5\\n\\n6\") #> [[1]] #> [1] \"1\" \"2\" #> #> [[2]] #> [1] \"3\" \"4\" \"5\" #> #> [[3]] #> [1] \"6\" #> # Only tokenize first two lines tokenize(\"1,2\\n3,4,5\\n\\n6\", n = 2) #> [[1]] #> [1] \"1\" \"2\" #> #> [[2]] #> [1] \"3\" \"4\" \"5\" #>"},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":null,"dir":"Reference","previous_headings":"","what":"Re-convert character columns in existing data frame — type_convert","title":"Re-convert character columns in existing data frame — type_convert","text":"useful need manual munging - can read columns character, clean (e.g.) regular expressions let readr take another stab parsing . name homage base utils::type.convert().","code":""},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Re-convert character columns in existing data frame — type_convert","text":"","code":"type_convert( df, col_types = NULL, na = c(\"\", \"NA\"), trim_ws = TRUE, locale = default_locale(), guess_integer = FALSE )"},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Re-convert character columns in existing data frame — type_convert","text":"df data frame. col_types One NULL, cols() specification, string. See vignette(\"readr\") details. NULL, column types imputed using rows. na Character vector strings interpret missing values. Set option character() indicate missing values. trim_ws leading trailing whitespace (ASCII spaces tabs) trimmed field parsing ? locale locale controls defaults vary place place. default locale US-centric (like R), can use locale() create locale controls things like default time zone, encoding, decimal mark, big mark, day/month names. guess_integer TRUE, guess integer types whole numbers, FALSE guess numeric type numbers.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Re-convert character columns in existing data frame — type_convert","text":"type_convert() removes 'spec' attribute, likely modifies column data types. (see spec() information column specifications).","code":""},{"path":"https://readr.tidyverse.org/dev/reference/type_convert.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Re-convert character columns in existing data frame — type_convert","text":"","code":"df <- data.frame( x = as.character(runif(10)), y = as.character(sample(10)), stringsAsFactors = FALSE ) str(df) #> 'data.frame':\t10 obs. of 2 variables: #> $ x: chr \"0.616355556994677\" \"0.304880728013813\" \"0.48939141863957\" \"0.148794440552592\" ... #> $ y: chr \"2\" \"3\" \"9\" \"1\" ... str(type_convert(df)) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> x = col_double(), #> y = col_double() #> ) #> 'data.frame':\t10 obs. of 2 variables: #> $ x: num 0.6164 0.3049 0.4894 0.1488 0.0696 ... #> $ y: num 2 3 9 1 6 8 5 4 7 10 df <- data.frame(x = c(\"NA\", \"10\"), stringsAsFactors = FALSE) str(type_convert(df)) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> x = col_double() #> ) #> 'data.frame':\t2 obs. of 1 variable: #> $ x: num NA 10 # Type convert can be used to infer types from an entire dataset # first read the data as character data <- read_csv(readr_example(\"mtcars.csv\"), col_types = list(.default = col_character()) ) str(data) #> spc_tbl_ [32 × 11] (S3: spec_tbl_df/tbl_df/tbl/data.frame) #> $ mpg : chr [1:32] \"21\" \"21\" \"22.8\" \"21.4\" ... #> $ cyl : chr [1:32] \"6\" \"6\" \"4\" \"6\" ... #> $ disp: chr [1:32] \"160\" \"160\" \"108\" \"258\" ... #> $ hp : chr [1:32] \"110\" \"110\" \"93\" \"110\" ... #> $ drat: chr [1:32] \"3.9\" \"3.9\" \"3.85\" \"3.08\" ... #> $ wt : chr [1:32] \"2.62\" \"2.875\" \"2.32\" \"3.215\" ... #> $ qsec: chr [1:32] \"16.46\" \"17.02\" \"18.61\" \"19.44\" ... #> $ vs : chr [1:32] \"0\" \"0\" \"1\" \"1\" ... #> $ am : chr [1:32] \"1\" \"1\" \"1\" \"0\" ... #> $ gear: chr [1:32] \"4\" \"4\" \"4\" \"3\" ... #> $ carb: chr [1:32] \"4\" \"4\" \"1\" \"1\" ... #> - attr(*, \"spec\")= #> .. cols( #> .. .default = col_character(), #> .. mpg = col_character(), #> .. cyl = col_character(), #> .. disp = col_character(), #> .. hp = col_character(), #> .. drat = col_character(), #> .. wt = col_character(), #> .. qsec = col_character(), #> .. vs = col_character(), #> .. am = col_character(), #> .. gear = col_character(), #> .. carb = col_character() #> .. ) #> - attr(*, \"problems\")= # Then convert it with type_convert type_convert(data) #> #> ── Column specification ────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> ) #> # A tibble: 32 × 11 #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows"},{"path":"https://readr.tidyverse.org/dev/reference/with_edition.html","id":null,"dir":"Reference","previous_headings":"","what":"Temporarily change the active readr edition — with_edition","title":"Temporarily change the active readr edition — with_edition","text":"with_edition() allows change active edition readr given block code. local_edition() allows change active edition readr end current function file.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/with_edition.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Temporarily change the active readr edition — with_edition","text":"","code":"with_edition(edition, code) local_edition(edition, env = parent.frame())"},{"path":"https://readr.tidyverse.org/dev/reference/with_edition.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Temporarily change the active readr edition — with_edition","text":"edition single integer, 1 2. code Code run changed edition. env Environment controls scope changes. expert use .","code":""},{"path":"https://readr.tidyverse.org/dev/reference/with_edition.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Temporarily change the active readr edition — with_edition","text":"","code":"with_edition(1, edition_get()) #> [1] 1 with_edition(2, edition_get()) #> [1] 2 # readr 1e and 2e behave differently when input rows have different number # number of fields with_edition(1, read_csv(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\"))) #> Warning: 1 parsing failure. #> row col expected actual file #> 1 -- 3 columns 2 columns literal data #> # A tibble: 2 × 3 #> X Y Z #> #> 1 1 2 NA #> 2 3 4 5 with_edition(2, read_csv(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\"))) #> Warning: One or more parsing issues, call `problems()` on your data frame for #> details, e.g.: #> dat <- vroom(...) #> problems(dat) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): X #> num (1): Y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> X Y #> #> 1 1 2 #> 2 3 45 # local_edition() applies in a specific scope, for example, inside a function read_csv_1e <- function(...) { local_edition(1) read_csv(...) } read_csv(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\")) # 2e behaviour #> Warning: One or more parsing issues, call `problems()` on your data frame for #> details, e.g.: #> dat <- vroom(...) #> problems(dat) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): X #> num (1): Y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> X Y #> #> 1 1 2 #> 2 3 45 read_csv_1e(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\")) # 1e behaviour #> Warning: 1 parsing failure. #> row col expected actual file #> 1 -- 3 columns 2 columns literal data #> # A tibble: 2 × 3 #> X Y Z #> #> 1 1 2 NA #> 2 3 4 5 read_csv(\"1,2\\n3,4,5\", col_names = c(\"X\", \"Y\", \"Z\")) # 2e behaviour #> Warning: One or more parsing issues, call `problems()` on your data frame for #> details, e.g.: #> dat <- vroom(...) #> problems(dat) #> Rows: 2 Columns: 2 #> ── Column specification ────────────────────────────────────────────────── #> Delimiter: \",\" #> dbl (1): X #> num (1): Y #> #> ℹ Use `spec()` to retrieve the full column specification for this data. #> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message. #> # A tibble: 2 × 2 #> X Y #> #> 1 1 2 #> 2 3 45"},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":null,"dir":"Reference","previous_headings":"","what":"Write a data frame to a delimited file — write_delim","title":"Write a data frame to a delimited file — write_delim","text":"write_*() family functions improvement analogous function write.csv() approximately twice fast. Unlike write.csv(), functions include row names column written file. generic function, output_column(), applied variable coerce columns suitable output.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Write a data frame to a delimited file — write_delim","text":"","code":"write_delim( x, file, delim = \" \", na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_csv( x, file, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_csv2( x, file, na = \"NA\", append = FALSE, col_names = !append, quote = c(\"needed\", \"all\", \"none\"), escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_excel_csv( x, file, na = \"NA\", append = FALSE, col_names = !append, delim = \",\", quote = \"all\", escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_excel_csv2( x, file, na = \"NA\", append = FALSE, col_names = !append, delim = \";\", quote = \"all\", escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() ) write_tsv( x, file, na = \"NA\", append = FALSE, col_names = !append, quote = \"none\", escape = c(\"double\", \"backslash\", \"none\"), eol = \"\\n\", num_threads = readr_threads(), progress = show_progress(), path = deprecated(), quote_escape = deprecated() )"},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Write a data frame to a delimited file — write_delim","text":"x data frame tibble write disk. file File connection write . delim Delimiter used separate values. Defaults \" \" write_delim(), \",\" write_excel_csv() \";\" write_excel_csv2(). Must single character. na String used missing values. Defaults NA. Missing values never quoted; strings value na always quoted. append FALSE, overwrite existing file. TRUE, append existing file. cases, file exist new file created. col_names FALSE, column names included top file. TRUE, column names included. specified, col_names take opposite value given append. quote handle fields contain characters need quoted. needed - Values quoted needed: contain delimiter, quote, newline. - Quote fields. none - Never quote fields. escape type escape use quotes data. double - quotes escaped doubling . backslash - quotes escaped preceding backslash. none - quotes escaped. eol end line character use. commonly either \"\\n\" Unix style newlines, \"\\r\\n\" Windows style newlines. num_threads Number threads use reading materializing vectors. data contains newlines within fields parser automatically forced use single thread . progress Display progress bar? default display interactive session knitting document. display updated every 50,000 values display estimated reading time 5 seconds . automatic progress bar can disabled setting option readr.show_progress FALSE. path Use file argument instead. quote_escape Use escape argument instead.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Write a data frame to a delimited file — write_delim","text":"write_*() returns input x invisibly.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"output","dir":"Reference","previous_headings":"","what":"Output","title":"Write a data frame to a delimited file — write_delim","text":"Factors coerced character. Doubles formatted decimal string using grisu3 algorithm. POSIXct values formatted ISO8601 UTC timezone Note: POSIXct objects local non-UTC timezones converted UTC time writing. columns encoded UTF-8. write_excel_csv() write_excel_csv2() also include UTF-8 Byte order mark indicates Excel csv UTF-8 encoded. write_excel_csv2() write_csv2 created allow users different locale settings save .csv files using default settings (e.g. ; column separator , decimal separator). common European countries. Values quoted contain comma, quote newline. write_*() functions automatically compress outputs appropriate extension given. Three extensions currently supported: .gz gzip compression, .bz2 bzip2 compression .xz lzma compression. See examples information.","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Write a data frame to a delimited file — write_delim","text":"Florian Loitsch, Printing Floating-Point Numbers Quickly Accurately Integers, PLDI '10, http://www.cs.tufts.edu/~nr/cs257/archive/florian-loitsch/printf.pdf","code":""},{"path":"https://readr.tidyverse.org/dev/reference/write_delim.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Write a data frame to a delimited file — write_delim","text":"","code":"# \\dontshow{ .old_wd <- setwd(tempdir()) # } # If only a file name is specified, write_()* will write # the file to the current working directory. write_csv(mtcars, \"mtcars.csv\") write_tsv(mtcars, \"mtcars.tsv\") # If you add an extension to the file name, write_()* will # automatically compress the output. write_tsv(mtcars, \"mtcars.tsv.gz\") write_tsv(mtcars, \"mtcars.tsv.bz2\") write_tsv(mtcars, \"mtcars.tsv.xz\") # \\dontshow{ setwd(.old_wd) # }"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-development-version","dir":"Changelog","previous_headings":"","what":"readr (development version)","title":"readr (development version)","text":"major user-facing changes. Patch release housekeeping changes internal changes requested CRAN around format specification compiled code.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-214","dir":"Changelog","previous_headings":"","what":"readr 2.1.4","title":"readr 2.1.4","text":"CRAN release: 2023-02-10 user-facing changes. Patch release internal changes requested CRAN.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-213","dir":"Changelog","previous_headings":"","what":"readr 2.1.3","title":"readr 2.1.3","text":"CRAN release: 2022-10-01 Help files man/ re-generated, give rise valid HTML5. (impetus release, keep package safely CRAN.) mini-gapminder-africa.csv friends new example datasets accessible via readr_example(), added illustrate reading multiple files , single data frame.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-212","dir":"Changelog","previous_headings":"","what":"readr 2.1.2","title":"readr 2.1.2","text":"CRAN release: 2022-01-30 read_table(), read_log(), read_delim_chunked() (friends) gain show_col_types argument found elsewhere. read_*() functions now respect show_col_types argument option, even using first edition parsing engine (#1331). show_progress() uses rlang::is_interactive() instead base::interactive() (#1356). read_builtin() argument checking, catch obviously malformed input passing along utils::data() (#1361). chickens.csv whitespace-sample.txt new example datasets accessible via readr_example() (#1354).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-211","dir":"Changelog","previous_headings":"","what":"readr 2.1.1","title":"readr 2.1.1","text":"CRAN release: 2021-11-30 Jenny Bryan now maintainer. Fix buffer overflow trying parse integer field 64 characters long (#1326)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-210","dir":"Changelog","previous_headings":"","what":"readr 2.1.0","title":"readr 2.1.0","text":"CRAN release: 2021-11-11 readr functions read eagerly default. Unfortunately many users experienced frustration drawbacks lazy reading, particular locking files Windows, decided disable lazy reading default. However options(readr.read_lazy = TRUE) can used set default lazy desired. New readr.read_lazy global option control readr reads files lazily (#1266)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-202","dir":"Changelog","previous_headings":"","what":"readr 2.0.2","title":"readr 2.0.2","text":"CRAN release: 2021-09-27 minor test tweak compatibility testthat 3.1.0 (#@lionel-, #1304) write_rds() gains text= argument, control using text based object representation, like ascii= argument saveRDS() (#1270)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-201","dir":"Changelog","previous_headings":"","what":"readr 2.0.1","title":"readr 2.0.1","text":"CRAN release: 2021-08-10 options(readr.show_col_types = FALSE) now works intended (#1250) read_delim_chunked() now correctly respects chunk_size parameter (#1248) type_convert() gains guess_integer argument, passed guess_parser() (@jmbarbone, #1264) read_tsv() now correctly passes quote na arguments vroom::vroom() (#1254, #1255) Avoid spurious byte compilation errors due programmatically generated spec_*() functions.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-200","dir":"Changelog","previous_headings":"","what":"readr 2.0.0","title":"readr 2.0.0","text":"CRAN release: 2021-07-20","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"second-edition-changes-2-0-0","dir":"Changelog","previous_headings":"","what":"second edition changes","title":"readr 2.0.0","text":"readr 2.0.0 major release readr introduces new second edition parsing writing engine implemented via vroom package. engine takes advantage lazy reading, multi-threading performance characteristics modern SSD drives significantly improve performance reading writing compared first edition engine. continue support first edition number releases, eventually support first deprecated removed. can use with_edition() local_edition() functions temporarily change edition readr section code. e.g. with_edition(1, read_csv(\"my_file.csv\")) read my_file.csv first edition readr. readr::local_edition(1) placed top function script use first edition rest function script.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"lazy-reading-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Lazy reading","title":"readr 2.0.0","text":"Edition two uses lazy reading default. first call read_*() function delimiters newlines throughout entire file found, data actually read used program. can provide substantial speed improvements reading character data. particularly useful interactive exploration subset full dataset. However also means problematic values necessarily seen immediately, actually read. warning issued first time problem encountered, may happen initial reading. Run problems() dataset read entire dataset return problems found. Run problems(lazy = TRUE) want retrieve problems found far. Deleting files reading also impacted laziness. Windows open files deleted long process file open. readr keeps file open reading lazily means read, immediately delete file. readr cases close file completely read. However, know want able delete file reading best pass lazy = FALSE reading file.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"reading-multiple-files-at-once-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Reading multiple files at once","title":"readr 2.0.0","text":"Edition two built-support reading sets files columns one output table single command. Just pass filenames read vector reading function. First generate files read splitting nycflights dataset airline. can efficiently read one tibble passing filenames directly readr. filenames contain data, date sample collected, use id argument include paths column data. likely post-process paths keep relevant portion use case.","code":"library(nycflights13) purrr::iwalk( split(flights, flights$carrier), ~ { .x$carrier[[1]]; vroom::vroom_write(.x, glue::glue(\"flights_{.y}.tsv\"), delim = \"\\t\") } ) files <- fs::dir_ls(glob = \"flights*tsv\") files readr::read_tsv(files)"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"delimiter-guessing-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Delimiter guessing","title":"readr 2.0.0","text":"Edition two supports automatic guessing delimiters. can now use read_delim() without specifying delim argument many cases.","code":"x <- read_delim(readr_example(\"mtcars.csv\"))"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"literal-data-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Literal data","title":"readr 2.0.0","text":"edition one reading functions treated input newline vectors length > 1 literal data. edition two vectors length > 1 now assumed correspond multiple files. now explicit way represent literal data, putting () around input.","code":"readr::read_csv(I(\"a,b\\n1,2\"))"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"license-changes-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"License changes","title":"readr 2.0.0","text":"systematically re-licensing tidyverse r-lib packages use MIT license, make package licenses clear permissive possible. end readr vroom packages now released MIT license.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"deprecated-or-superseded-functions-and-features-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Deprecated or superseded functions and features","title":"readr 2.0.0","text":"melt_csv(), melt_delim(), melt_tsv() melt_fwf() superseded functions name meltr package. versions readr deprecated. functions rely first edition parsing code challenging update new parser. first edition parsing code eventually removed readr removed. read_table2() renamed read_table(), users expect read_table() work like utils::read.table(). want previous strict behavior read_table() can use read_fwf() fwf_empty() directly (#717). Normalizing newlines files just carriage returns \\r longer supported. last major OS use CR newline ‘classic’ Mac OS, final release 2001.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"other-second-edition-changes-2-0-0","dir":"Changelog","previous_headings":"second edition changes","what":"Other second edition changes","title":"readr 2.0.0","text":"read_*_chunked() functions now include specification attribute (#1143) read_*() functions gain col_select argument easily choose columns select. read_*() functions gain id argument optionally store file paths reading multiple files. read_*() functions gain name_repair argument control column names repaired. read_*() write_*() functions gain num_threads argument control number processing threads use (#1201) write_*() format_*() functions gain quote escape arguments, explicitly control fields quoted double quotes escaped. (#653, #759, #844, #993, #1018, #1083) write_*() functions gain progress argument display progress bar writing (#791). write_excel_csv() now defaults quote = \"\" (#759) write_tsv() now defaults quote = \"none\" (#993) read_table() now handles skipped lines unpaired quotes properly (#1180)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"additional-features-and-fixes-2-0-0","dir":"Changelog","previous_headings":"","what":"Additional features and fixes","title":"readr 2.0.0","text":"BH package longer dependency. boost C++ headers BH thousands files, can take long time extract compiling takes great deal memory, made readr difficult compile systems limited memory (#1147). readr now uses tzdb package parsing date-times (@DavisVaughan, r-lib/vroom#273) Chunked readers now support files INT_MAX (~ 2 Billion) number lines (#1177) Memory longer inadvertently leaks reading memory R connections (#1161) Invalid date formats longer can potentially crash R (#1151) col_factor() now throws informative error message given non-character levels (#1140) problems() now takes .Last.value default argument. lets run problems() without argument see problems previously read dataset. read_delim() fails sample parsing problems contains non-ASCII characters (@hidekoji, #1136) read_log() gains trim_ws argument (#738) read_rds() write_rds() gain refhook argument, pass functions handle references objects (#1206) read_rds() can now read .Rds files URLs (#1186) read_*() functions gain show_col_types argument, set FALSE turns showing column types unconditionally. type_convert() now throws warning input character columns (#1020) write_csv() now errors given matrix column (#1171) write_csv() now able write data duplicated column names (#1169) write_file() now forces argument opening output file (#1158)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-140","dir":"Changelog","previous_headings":"","what":"readr 1.4.0","title":"readr 1.4.0","text":"CRAN release: 2020-10-05","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"breaking-changes-1-4-0","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"readr 1.4.0","text":"write_*() functions first argument now file instead path, consistency read_*() functions. path deprecated removed future version readr (#1110, @brianrice2) write_*() functions now output NaN values way NA values, controlled na= argument. (#1082).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"new-features-1-4-0","dir":"Changelog","previous_headings":"","what":"New features","title":"readr 1.4.0","text":"now possible generate column specification tibble (data.frame) .col_spec() convert column specification short representation .character() cli package now used messages. runtime performance tables extreme number columns greatly improved (#825) Compressed files now detected magic numbers rather file extension (#1125) memory leak reading files now fixed (#1092) write_*() functions gain eol = argument control end line character used (#857). allows writing CSV files Windows newlines (CRLF) desired. Rcpp dependency removed favor cpp11. build system greatly simplified work systems.","code":"s <- as.col_spec(iris) s #> cols( #> Sepal.Length = col_double(), #> Sepal.Width = col_double(), #> Petal.Length = col_double(), #> Petal.Width = col_double(), #> Species = col_factor(levels = c(\"setosa\", \"versicolor\", \"virginica\"), ordered = FALSE, include_na = FALSE) #> ) as.character(s) #> [1] \"ddddf\""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"additional-features-and-fixes-1-4-0","dir":"Changelog","previous_headings":"","what":"Additional features and fixes","title":"readr 1.4.0","text":"full problem field now displayed problems tibble, intended (#444). New %h placeholder parsing unrestricted hours (<0 >23) support parsing durations (#549, @krlmlr). .character.col_spec() now handles logical columns well (#1127) fwf_positions(end) longer default argument must specified (#996) guess_parser() gains na argument removes NA values guessing (#1041). parse_guess() now passes na argument guess_parser() read_* functions now close properly connections, including errors like HTTP errors reading url (@cderv, #1050). read_delimited() longer mistakenly stats literal filenames (#1063) read_lines() now ignores quotations skipping lines (#991). read_lines(skip_empty_rows = TRUE) longer crashes file ends empty line (#968) write_*() functions now invisibly return input data frame unchanged, rather version factors dates converted strings. (@jesse-ross, #975). write_csv2() now formats decimal numbers consistently utils::write.csv2() (#1087) write_csv2() format_csv2() longer pad number columns whitespaces (@keesdeschepper, #1046). write_excel_csv() longer outputs byte order mark appending file (#1075). Uses tibble::data_frame updated tibble::tibble (tidyverse/dplyr#4069, @thays42, #1124, @brianrice2) read_delimited() now returns empty tibble::data_frame() rather signaling error given connection empty file (@pralitp, #963). helpful error trying write data frames list columns (@ellessenne, #938) type_convert() removes ‘spec’ attribute, current columns likely modified data types. ‘spec’ attribute set functions like read_delim() (@jimhester, @wibeasley, #1032). write_rds() now can specify Rds version use. default value 2 ’s compatible R versions prior 3.5.0 (@shrektan, #1001). Fixes issues related variable initialization C++ code (@michaelquinn32, ##1133).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-131","dir":"Changelog","previous_headings":"","what":"readr 1.3.1","title":"readr 1.3.1","text":"CRAN release: 2018-12-21 Column specifications now coloured printed. makes easy see glance column input different type rest. Colouring can disabled setting options(crayon.enabled = FALSE). .col_spec() can now use named character vectors, makes read_csv(\"file.csv\", col_types = c(xyz = \"c\")) equivalent read_csv(\"file.csv\", col_types = cols(xyz = col_character()) Fix skipping single quotes embedded double quoted strings, single quotes skipped commented lines (#944, #945). Fix compilation using custom architectures macOS (#919) Fix valgrind errors (#941)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-130","dir":"Changelog","previous_headings":"","what":"readr 1.3.0","title":"readr 1.3.0","text":"CRAN release: 2018-12-11","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"blank-line-skipping-1-3-0","dir":"Changelog","previous_headings":"Breaking Changes","what":"Blank line skipping","title":"readr 1.3.0","text":"readr’s blank line skipping modified consistent avoid edge cases affected behavior 1.2.0. skip parameter now behaves similar worked previous readr 1.2.0, addition parameter skip_blank_rows can used control fully blank lines skipped. (#923)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"tibble-data-frame-subclass-1-3-0","dir":"Changelog","previous_headings":"Breaking Changes","what":"tibble data frame subclass","title":"readr 1.3.0","text":"readr 1.3.0 returns results spec_tbl_df subclass. differs regular tibble spec attribute (holds column specification) lost soon object subset (normal tbl_df object returned). Historically tbl_df’s lost attributes subset. However recent versions tibble retain attributes subetting, spec_tbl_df subclass needed ensure previous behavior. break compatibility explicitly checking class returned object. way get backwards compatible behavior call subset arguments object, e.g. x[].","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"bugfixes-1-3-0","dir":"Changelog","previous_headings":"","what":"Bugfixes","title":"readr 1.3.0","text":"hms objects NA values now written without whitespace padding (#930). read_*() functions now return spec_tbl_df objects, differ regular tbl_df objects spec attribute removed (demoted regular tbl_df objects) soon subset (#934). write_csv2() now properly respects na argument (#928) Fixes compilation multiple architectures linux (#922). Fixes compilation R < 3.3.0","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-121","dir":"Changelog","previous_headings":"","what":"readr 1.2.1","title":"readr 1.2.1","text":"CRAN release: 2018-11-22 release skips clipboard tests CRAN servers","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-120","dir":"Changelog","previous_headings":"","what":"readr 1.2.0","title":"readr 1.2.0","text":"CRAN release: 2018-11-22","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"integer-column-guessing-1-2-0","dir":"Changelog","previous_headings":"Breaking Changes","what":"Integer column guessing","title":"readr 1.2.0","text":"readr functions longer guess columns type integer, instead columns guessed numeric. R uses 32 bit integers 64 bit doubles integers can stored doubles, guaranteeing loss information. change made remove errors numeric columns incorrectly guessed integers. know certain column integer like read can specifying column type explicitly col_types argument.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"blank-line-skipping-1-2-0","dir":"Changelog","previous_headings":"Breaking Changes","what":"Blank line skipping","title":"readr 1.2.0","text":"readr now always skips blank lines automatically parsing, may change number lines need pass skip parameter. instance file one blank line two lines want skip previously pass skip = 3, now need pass skip = 2.","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"melt-functions-1-2-0","dir":"Changelog","previous_headings":"New features","what":"Melt functions","title":"readr 1.2.0","text":"now family melt_*() functions readr. functions store data ‘long’ ‘melted’ form, row corresponds single value dataset. form useful data ragged rectangular. Thanks Duncan Garmonsway (@nacnudus) great work idea implementation melt_*() functions!","code":"data <-\"a,b,c 1,2 w,x,y,z\" readr::melt_csv(data) #> # A tibble: 9 x 4 #> row col data_type value #> #> 1 1 1 character a #> 2 1 2 character b #> 3 1 3 character c #> 4 2 1 integer 1 #> 5 2 2 integer 2 #> 6 3 1 character w #> 7 3 2 character x #> 8 3 3 character y #> 9 3 4 character z"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"connection-improvements-1-2-0","dir":"Changelog","previous_headings":"New features","what":"Connection improvements","title":"readr 1.2.0","text":"readr 1.2.0 changes R connections parsed readr. previous versions readr connections read -memory raw vector, passed readr functions. made reading connections small medium datasets fast, also meant dataset fit memory least twice (raw data, parsed data). also meant reading begin full vector read connection. Now instead write connection temporary file (R temporary directory), parse temporary file. means connections may take little longer read, also means longer need fit memory. also allows use chunked readers process data parts. Future improvements readr allow parse data connections streaming fashion, avoid many drawbacks either method.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"additional-new-features-1-2-0","dir":"Changelog","previous_headings":"New features","what":"Additional new features","title":"readr 1.2.0","text":"melt_*() functions added reading ragged data (#760, @nacnudus). AccumulateCallback R6 class added provide example accumulating values single result (#689, @blakeboswell). read_fwf() can now accept overlapping field specifications (#692, @gergness) type_convert() now allows character column specifications also silently skips non-character columns (#369, #699) parse_*() functions read_fwf() gain trim_ws argument control whether fields trimmed parsing (#636, #735). parse_number() now parses numbers scientific notation using e E (#684, @sambrady3). Add write_excel_csv2() function allow writing csv files comma decimal separator semicolon column separator (#753, @olgamie). read_*() files now support reading clipboard using clipboard() (#656). write_file() gains sep argument, specify line separator (#665). Allow files read via FTP SSH recognising sftp URL protocol (#707, @jdeboer). parse_date*() accepts%` local day week (#763, @tigertoes). Added function read_lines_raw_chunked() (#710, @gergness) write_csv2() added complement write_excel_csv2() allow writing csv file readable read_csv2() (#870, @cderv). .col_spec() now exported (#517). write*() functions gain quote_escape argument control quotes escaped output (#854). read*() functions now informative error trying read remote bz2 file (#891). spec_table2() function added correspond read_table2() (#778, @mawds). parse_factor() now levels = NULL default (#862, @mikmart). \"f\" can now used shortcode col_factor() cols() col_types argument read_delim() friends (#810, @mikmart). Functions now read connections temporary file rather -memory object (#610, #76).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"bug-fixes-1-2-0","dir":"Changelog","previous_headings":"","what":"Bug Fixes","title":"readr 1.2.0","text":"standardise_path() now uses case-insensitive comparison file extensions (#794). parse_guess() now guesses logical types given (lowercase) ‘true’ ‘false’ inputs (#818). read_*() now print progress bar running inside RStudio notebook chunk (#793) read_table2() now skips comments anywhere file (#908). parse_factor() now handles case empty strings separately, can factor level empty string (#864). read_delim() now correctly reads quoted headers embedded newlines (#784). fwf_positions() now always returns col_names character (#797). format_*() now explicitly marks ’s output encoding UTF-8 (#697). read_delim() now ignores whitespace delimiter quoted fields (#668). read_table2() now properly ignores blank lines end file like read_table() read_delim() (#657). read_delim(), read_table() read_table() now skip blank lines start file (#680, #747). guess_parser() now guesses logical type columns missing. useful binding multiple files together files missing columns. (#662). Column guessing now never guess integer type. avoids issues double columns incorrectly guessed integers integer values first 1000 (#645, #652). read_*() now converts string files UTF-8 parsing, convenient non-UTF-8 platforms cases (#730, @yutannihilation). write_csv() writes integers 10^15 without scientific notation (#765, @zeehio) read_*() longer throws “length NULL changed” warning trying resize skipped column (#750, #833). read_*() now handles non-ASCII paths properly R >=3.5.0 Windows (#838, @yutannihilation). read*()’s trim_ws parameter now trims spaces tabs (#767)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-111","dir":"Changelog","previous_headings":"","what":"readr 1.1.1","title":"readr 1.1.1","text":"CRAN release: 2017-05-16 Point release test compatibility tibble v1.3.1. Fixed undefined behavior localtime.c using locale(tz = \"\") loading timezone due incomplete reinitialization global locale.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-110","dir":"Changelog","previous_headings":"","what":"readr 1.1.0","title":"readr 1.1.0","text":"CRAN release: 2017-03-22","code":""},{"path":[]},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"parser-improvements-1-1-0","dir":"Changelog","previous_headings":"New features","what":"Parser improvements","title":"readr 1.1.0","text":"parse_factor() gains include_na argument, include NA factor levels (#541). parse_factor() now can accept levels = NULL, allows one generate factor levels based data (like stringsAsFactors = TRUE) (#497). parse_numeric() now returns full string contains numbers (#548). parse_time() now correctly handles 12 /PM (#579). problems() now returns file path additional location error file (#581). read_csv2() gives message updates default locale (#443, @krlmlr). read_delim() now signals error given empty delimiter (#557). write_*() functions witting whole number doubles longer written trailing .0 (#526).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"whitespace--fixed-width-improvements-1-1-0","dir":"Changelog","previous_headings":"New features","what":"Whitespace / fixed width improvements","title":"readr 1.1.0","text":"fwf_cols() allows specifying col_positions argument read_fwf() named arguments either column positions widths (#616, @jrnold). fwf_empty() gains n argument control many lines read whitespace determine column structure (#518, @Yeedle). read_fwf() gives error message specifications overlapping columns (#534, @gergness) read_table() can now handle pipe() connections (#552). read_table() can now handle files many lines leading comments (#563). read_table2() allows number whitespace characters delimiters, exact replacement utils::read.table() (#608).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"writing-to-connections-1-1-0","dir":"Changelog","previous_headings":"","what":"Writing to connections","title":"readr 1.1.0","text":"write_*() functions now support writing binary connections. addition output filenames .gz, .bz2 .xz automatically open appropriate connection write compressed file. (#348) write_lines() now accepts list raw vectors (#542).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"miscellaneous-features-1-1-0","dir":"Changelog","previous_headings":"","what":"Miscellaneous features","title":"readr 1.1.0","text":"col_euro_double(), parse_euro_double(), col_numeric(), parse_numeric() removed. guess_encoding() returns tibble, works better lists raw vectors (returned read_lines_raw()). ListCallback R6 Class provide flexible return type callback functions (#568, @mmuurr) tibble::.tibble() now used construct tibbles (#538). read_csv, read_csv2, read_tsv gain quote argument, (#631, @noamross)","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"bugfixes-1-1-0","dir":"Changelog","previous_headings":"","what":"Bugfixes","title":"readr 1.1.0","text":"parse_factor() now converts data UTF-8 based supplied locale (#615). read_*() functions guess_max argument now throw errors inappropriate inputs (#588). read_*_chunked() functions now properly end stream FALSE returned callback. read_delim() read_fwf() columns skipped using col_types now report correct column name (#573, @cb4ds). spec() declarations long now print properly (#597). read_table() print spec col_types NULL (#630, @jrnold). guess_encoding() now returns tibble ASCII input well (#641).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-100","dir":"Changelog","previous_headings":"","what":"readr 1.0.0","title":"readr 1.0.0","text":"CRAN release: 2016-08-03","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"column-guessing-1-0-0","dir":"Changelog","previous_headings":"","what":"Column guessing","title":"readr 1.0.0","text":"process readr guesses types columns received substantial overhaul make easier fix problems initial guesses aren’t correct, make easier generate reproducible code. Now column specifications printing default read file: can extract values fact spec(): makes easier quickly identify parsing problems fix (#314). column specification long, new cols_condense() used condense spec identifying common type setting default. particularly useful handful columns different type (#466). can also generating initial specification without parsing file using spec_csv(), spec_tsv(), etc. figured correct column types file, ’s often useful make parsing strict. can either copying pasting printed output, long specs, saving spec disk write_rds(). production scripts, combine stop_for_problems() (#465): input data changes form, ’ll fail fast error. can now also adjust number rows readr uses guess column types guess_max: can now access guessing algorithm R. guess_parser() tell parser readr select character vector (#377). ’ve made number fixes guessing algorithm: New example extdata/challenge.csv carefully created cause problems default column type guessing heuristics. Blank lines lines comments now skipped automatically without warning (#381, #321). Single ‘-’ ‘.’ now parsed characters, numbers (#297). Numbers followed single trailing character parsed character, numbers (#316). now guess times using time_format specified locale(). made number improvements reification col_types, col_names actual data: col_types long, subsetted correctly (#372, @jennybc). col_names short, added names numbered correctly (#374, @jennybc). Missing column name names now given default name (X2, X7 etc) (#318). Duplicated column names now deduplicated. changes generate warning; suppress supply explicit col_names (setting skip = 1 ’s existing ill-formed header). col_types() accepts named list input (#401).","code":"challenge <- read_csv(readr_example(\"challenge.csv\")) #> Parsed with column specification: #> cols( #> x = col_integer(), #> y = col_character() #> ) spec(challenge) #> cols( #> x = col_integer(), #> y = col_character() #> ) challenge <- read_csv(readr_example(\"challenge.csv\"), guess_max = 1500) #> Parsed with column specification: #> cols( #> x = col_double(), #> y = col_date(format = \"\") #> )"},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"column-parsing-1-0-0","dir":"Changelog","previous_headings":"","what":"Column parsing","title":"readr 1.0.0","text":"date time parsers recognise three new format strings: %12 hour time format (#340). %AD %“automatic” date time parsers. slightly less flexible previous defaults. automatic date parser requires four digit year, accepts - / separators (#442). flexible time parser now requires colons hours minutes optional seconds (#424). %y %Y now strict require 2 4 characters respectively. Date time parsing functions received number small enhancements: parse_time() returns hms objects rather custom time class (#409). now correctly parses missing values (#398). parse_date() returns numeric vector (instead integer vector) (#357). parse_date(), parse_time() parse_datetime() gain na argument match parsers (#413). format argument omitted parse_date() parse_time(), date time formats specified locale used. now default %AD %respectively. can now parse partial dates parse_date() parse_datetime(), e.g. parse_date(\"2001\", \"%Y\") returns 2001-01-01. parse_number() slightly flexible - now parses numbers first ill-formed character. example parse_number(\"-3-\") parse_number(\"...3...\") now return -3 3 respectively. also fixed major bug parsing negative numbers yielded positive values (#308). parse_logical() now accepts 0, 1 well lowercase t, f, true, false.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"new-readers-and-writers-1-0-0","dir":"Changelog","previous_headings":"","what":"New readers and writers","title":"readr 1.0.0","text":"read_file_raw() reads complete file single raw vector (#451). read_*() functions gain quoted_na argument control whether missing values within quotes treated missing values strings (#295). write_excel_csv() can used write csv file UTF-8 BOM start, forces Excel read UTF-8 encoded (#375). write_lines() writes character vector file (#302). write_file() write single character raw vector file (#474). Experimental support chunked reading writing (read_*_chunked()) functions. API unstable subject change future (#427).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"minor-features-and-bug-fixes-1-0-0","dir":"Changelog","previous_headings":"","what":"Minor features and bug fixes","title":"readr 1.0.0","text":"Printing double values now uses implementation grisu3 algorithm speeds writing large numeric data frames ~10X. (#432) ‘.0’ appended whole number doubles, ensure read doubles well. (#483) readr imports tibble get consistent tbl_df behaviour (#317, #385). New example extdata/challenge.csv carefully created cause problems default column type guessing heuristics. default_locale() now sets default locale readr.default_locale rather regenerating call. (#416). locale() now automatically sets decimal mark set grouping mark. throws error accidentally set decimal grouping marks character (#450). read_*() can read long vectors, substantially increasing number rows can read (#309). read_*() functions return empty objects rather signaling error run empty file (#356, #441). read_delim() gains trim_ws argument (#312, noamross) read_fwf() received number improvements: read_fwf() now can now reliably read partial set columns (#322, #353, #469) fwf_widths() accepts negative column widths compatibility widths argument read.fwf() (#380, @leeper). can now read fixed width files ragged final columns, setting final end position fwf_positions() final width fwf_widths() NA (#353, @ghaarsma). fwf_empty() automatically. read_fwf() fwf_empty() can now skip commented lines setting comment argument (#334). read_lines() ignores embedded null’s strings (#338) gains na argument (#479). readr_example() makes easy access example files bundled readr. type_convert() now accepts NULL cols specification col_types (#369). write_delim() write_csv() now invisibly return input data frame (documented, #363). Doubles parsed boost::spirit::qi::long_double work around bug spirit library parsing large numbers (#412). Fix bug detecting column types single row files without headers (#333).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-022","dir":"Changelog","previous_headings":"","what":"readr 0.2.2","title":"readr 0.2.2","text":"CRAN release: 2015-10-22 Fix bug checking empty values missingness (caused valgrind issue random crashes).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-021","dir":"Changelog","previous_headings":"","what":"readr 0.2.1","title":"readr 0.2.1","text":"CRAN release: 2015-10-21 Fixes readr works Solaris.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"readr-020","dir":"Changelog","previous_headings":"","what":"readr 0.2.0","title":"readr 0.2.0","text":"CRAN release: 2015-10-19","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"internationalisation-0-2-0","dir":"Changelog","previous_headings":"","what":"Internationalisation","title":"readr 0.2.0","text":"readr now strategy dealing settings vary place place: locales. default locale still US centric (R ), can now easily override default timezone, decimal separator, grouping mark, day & month names, date format, encoding. lead number changes: read_csv(), read_tsv(), read_fwf(), read_table(), read_lines(), read_file(), type_convert(), parse_vector() gain locale argument. locale() controls input settings vary place--place. col_euro_double() parse_euro_double() deprecated. Use decimal_mark parameter locale() instead. default encoding now UTF-8. load files UTF-8, set encoding parameter locale() (#40). New guess_encoding() function uses stringi help figure encoding file. parse_datetime() parse_date() %B %b use month names (full abbreviate) defined locale (#242). also inherit tz locale, rather using explicit tz parameter. See vignette(\"locales\") details.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"file-parsing-improvements-0-2-0","dir":"Changelog","previous_headings":"","what":"File parsing improvements","title":"readr 0.2.0","text":"cols() lets pick default column type columns otherwise explicitly named (#148). can refer parsers either full name (e.g. col_character()) one letter abbreviation (e.g. c). cols_only() allows load named columns. can also choose override default column type cols() (#72). read_fwf() now much careful new lines. line short, ’ll get warning instead silent mistake (#166, #254). Additionally, last column can now ragged: width last field silently extended hits next line break (#146). appears common feature “fixed” width files wild. read_csv(), read_tsv(), read_delim() etc: comment argument allows ignore comments (#68). trim_ws argument controls whether leading trailing whitespace removed. defaults TRUE (#137). Specifying wrong number column names, rows unexpected number columns, generates warning, rather error (#189). Multiple NA values can specified passing character vector na (#125). default changed na = c(\"\", \"NA\"). Specifying na = \"\" now works expected character columns (#114).","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"column-parsing-improvements-0-2-0","dir":"Changelog","previous_headings":"","what":"Column parsing improvements","title":"readr 0.2.0","text":"Readr gains vignette(\"column-types\") describes defaults work override (#122). parse_character() gains better support embedded nulls: characters first null dropped warning (#202). parse_integer() parse_double() longer silently ignore trailing letters number (#221). New parse_time() col_time() allows parse times (hours, minutes, seconds) number seconds since midnight. format omitted, uses flexible parser looks hours, optional colon, minutes, optional colon, optional seconds, optional /pm (#249). parse_date() parse_datetime(): parse_datetime() longer incorrectly reads partial dates (e.g. 19, 1900, 1900-01) (#136). triggered common false positives re-reading ISO8601 spec, believe actually refer periods time, translated specific instant (#228). Compound formats “%D”, “%F”, “%R”, “%X”, “%T”, “%x” now parsed correctly, instead using ISO8601 parser (#178, @kmillar). “%.” now requires non-digit. New “%+” skips one non-digits. can now use %p refer /PM (/pm) (#126). %b %B formats (month abbreviated month name) ignore case matching (#219). Local (non-UTC) times without daylight savings now parsed correctly (#120, @andres-s). parse_number() somewhat flexible numeric parser designed read currencies percentages. reads first number string (using grouping mark defined locale). parse_numeric() deprecated name confusing - ’s flexible number parser, parser “numerics”, R collectively calls doubles integers. Use parse_number() instead. well improvements parser, ’ve also made number tweaks heuristics readr uses guess column types: New parse_guess() col_guess() explicitly guess column type. Bumped row inspection column typing guessing 100 1000. heuristics guessing col_integer() col_double() stricter. Numbers leading zeros now default parsed text, rather integers/doubles (#266). column guessed col_number() parses regular number ignoring grouping marks.","code":""},{"path":"https://readr.tidyverse.org/dev/news/index.html","id":"minor-improvements-and-bug-fixes-0-2-0","dir":"Changelog","previous_headings":"","what":"Minor improvements and bug fixes","title":"readr 0.2.0","text":"Now use R’s platform independent iconv wrapper, thanks BDR (#149). Pathological zero row inputs (due empty input, skip n_max) now return zero row data frames (#119). guessing field types, ’s information go , use character instead logical (#124, #128). Concise col_types specification now understands ? (guess) - (skip) (#188). count_fields() starts counting 1, 0 (#200). format_csv() format_delim() make easy render csv delimited file string. fwf_empty() now works correctly col_names supplied (#186, #222). parse_*() gains na argument allows specify values converted missing. problems() now reports column names rather column numbers (#143). Whenever problem, first five problems printing warning message, can easily see ’s wrong. read_*() throws warning instead error col_types specifies non-existent column (#145, @alyst). read_*() can read remote gz compressed file (#163). read_delim() defaults escape_backslash = FALSE escape_double = TRUE consistency. n_max also affects number rows read guess column types (#224). read_lines() gains progress bar. now also correctly checks interrupts every 500,000 lines can interrupt long running jobs. also correctly estimates number lines file, considerably speeding reading large files (60s -> 15s 1.5 Gb file). read_lines_raw() allows read file list raw vectors, one element line. type_convert() gains NA trim_ws arguments, removes missing values determining column types. write_csv(), write_delim(), write_rds() invisibly return input can use pipe (#290). write_delim() generalises write_csv() write delimited format (#135). write_tsv() helpful wrapper tab separated files. Quotes used ’re needed (#116): string contains quote, delimiter, new line NA. Double vectors saved using amount precision .character() (#117). New na argument specifies missing values written (#187) POSIXt vectors saved ISO8601 compatible format (#134). longer fails silently can’t open target writing (#193, #172). write_rds() read_rds() wrap around readRDS() saveRDS(), defaulting compression (#140, @nicolasCoutin).","code":""}]