recap.R

# Libraries needed ---------------------------------------------------------

library(tidyverse)

# Recap: Import and Visualisations ----------------------------------------

# 1. Import mpg.csv from the data_raw directory
# 2. Create a box plot of the fuel efficiency in the city (cty) for each class of car (class)
# 3. Do 1 and 2 in a pipe without saving any value to the environment and facet_wrap it cyl
# 4. Which cylinder count has the biggest variance for which class of car?

# Recap: Data Transformation ----------------------------------------------

# For the following exercise you can either create a pipe or do it step by step

# 1. Import flights.csv from the data_raw directory
# 2. Create a smaller data set that only includes flights leaving on "May the Fourth"
# 3. Normalise  sched_dep_time colum so it represents minutes past midnight
# 4. Create a new column with the information of whether a flight was cancelled
# 5. How many minutes past midnight was the earliest flight scheduled, 
#    when was the earliest cancelled flight scheduled?