- Notes:
- Tentative calendar (weekly topics), subject to changes depending on the pace of the course.
- Labs: For the covered topics in a given week, the associated lab takes place on Th/Fr of the current week.
- Dates: Aug 23-25
- Topics: Introduction, policies/logistics, and course in a nutshell.
- Lecture material
- About the Course (slides)
- Introduction: Big Picture (slides)
- Lab: No lab
- Reading:
- Course policies, and FAQs
- To Do:
- Dates: Aug 28-Sep 01:
- Topics: Getting started with R, and comprehensive review of the RStudio workspace.
- Lecture material
- About R (slides)
- First contact with R (tutorial)
- Intro to Rmd files (tutorial)
- Data Types and Vectors (slides)
- Lab material:
- Reading:
- Markdown tutorial by CommonMark
- www.markdowntutorial.com/
- Introduction to R Markdown by RStudio
- Cheat sheet:
- WARM-UP 1: due Sep-09
- Dates: Sep 04-08 (Holiday Sep-04)
- Topics: Getting to know R vectors and concepts like atomicity, vectorization, recycling, and subsetting.
- Lecture material
- Intro to vectors (tutorial)
- Arrays and Factors (slides)
- Lists (slides)
- Lab material:
- Reading:
- chapter 20: Vectors from R for Data Science by Grolemund and Wickham.
- WARM-UP 2: due Sep-16
- Dates: Sep 11-15
- Topics: Fundamental low-level stuff for the rest of the course.
- Lecture material
- Filesystem Basics (slides)
- Shell Basics (slides)
- Git Basics (slides)
- Lab material:
- Reading:
- Read sections 4 to 9 in Part I Installation from Happy Git and GitHub for the useR by Jenny Bryan et al.
- Cheat sheet:
- Dates: Sep 18-22
- Topics: Data Tables, typical storage formats, and relation with data frames.
- Lecture material
- Data Tables (slides)
- Importing Tables in R (slides)
- Data Frames (slides)
- Lab material:
- Reading:
- Organizing data in spreadsheets by Karl Broman
- Cheat sheet:
- HW 1: due Sep-24
- Dates: Sep 25-29
- Topics: Data wrangling (reshaping, aggregating) with
"dplyr", and graphs with"ggplot2". - Lecture Material
- Introduction to the R package
"dplyr"(slides by Hadley Wickham) - Introduction to
"dplyr"(tutorial) - Introduction to the R package
"ggplot2"(slides) - "ggplot2" lecture (slides by Karthik Ram)
- Introduction to the R package
- Lab material:
- Reading:
- Introduction to dplyr introductory vignette by Hadley Wickham
- Cheat sheet:
- HW 2: due Oct-02
- Dates: Oct 02-06
- Topics: More
"dplyr","ggplot2", and file structure - Lecture Material
- Data pipelines in
"dplyr" - Mini project (slides)
- Introduction to PCA (slides) and live demo.
- Data pipelines in
- Lab material:
- Reading:
- Tidy Data by Hadley Wickham RStudio).
- Dates: Oct 09-13
- Topics: Basics of Functions, R expressions, and conditionals.
- Lecture Material
- Introduction to functions (tutorial)
- Introduction to R expressions and conditionals (tutorial)
- Lab material:
- Reading:
- chapter 19: Functions from R for Data Science by Grolemund and Wickham.
- HW 3: due Oct-15
- MIDTERM 1: Fri Oct-13
- Dates: Oct 16-20
- Topics: Basics of loops, and intro to
"shiny"apps. - Lecture Material
- Introduction to loops (tutorial)
- More about functions (tutorial)
- Introduction to shiny apps (slides)
- Lab material:
- Reading:
- chapter 21: Iteration from R for Data Science by Grolemund and Wickham.
- How to Start Shiny tutorial by Garret Grolemund
- Cheat sheet:
- Dates: Oct 23-27
- Topics: R andom numbers, sampling, and monte carlo simulation.
- Lecture Material
- Introduction to random numbers
- More Simulations
- Shiny Tutorial by Gerret Grolemund
- Lab material:
- Reading:
- Cheat sheet:
- Dates: Oct 30-Nov 03
- Topics: Introduction to character strings and their basic manipulations.
- Lecture Material
- String Basics (slides)
- Intro to Strings (tutorial)
- Getting started with testing by Wickham
- Lab material:
- Reading:
- Handling Strings in R by GS.
- chapter 14: Strings from R for Data Science by Grolemund and Wickham.
- HOMEWORK: Post 1 due Oct-31
- Dates: Nov 06-10
- Topics: Introduction to Regular Expressions.
- Lecture Material
- Introduction to regular expressions
- Regexpal tester tool.
- Lab material:
- No lab (veteran's day)
- Reading:
- Handling Strings in R by GS.
- Cheat sheet:
- Dates: Nov 13-17
- Topics: More about Regular Expressions and coding habits.
- Lecture Material
- Lab material:
- Reading:
- Handling Strings in R by GS.
- Cheat sheet:
- HOMEWORK: Problem Set 4 due Nov-26
- Dates: Nov 20-24
- Topics: Data visualization and the DAC
- Lecture Material
- Comments on Data Visualization and the Data Analysis Cycle (chalk and talk).
- Dates: Nov 27-Dec 01
- Topics: Introduction to XML and webscraping
- Lecture Material
- Lab material:
- HOMEWORK: Post 2 due Nov-30
- Dates: Dec 04-08
- Topics: Prepare for final examination
- Lecture Material
- No lecture. Instructor will hold OH (4-5pm in 309 Evans)
- FINAL: Friday Dec-15th, 8-11am (room TBA)