library(tidyverse)
library(readxl)
Part 1: Excel to CSV Workflow
Step 1: Read the Data
- Read in the Excel file called
favourite-food.xlsx from
the data-raw/ folder.
fav_food <- read_excel(___)
fav_food
Step 2: Clean the Data
- Clean up the missing data (
NAs) and make sure you’re
happy with variable types. Modify the read_excel function
to take care of these issues.
fav_food <- read_excel(___, ___)
fav_food
- Convert the SES (socioeconomic status) to a factor variables with
levels in the following order:
Low, Middle,
High.
# add code here
Step 3: Save to CSV
- Write out the resulting data frame to
favourite-food.csv in the data/ folder.
# add code here
Step 5: Verify CSV Data
- Finally, read
favourite-food.csv back in from the
data/ folder and observe the variable types. Are they as
you left them?
# add code here
Part 2: Excel to RDS Workflow
Step 1: Read the Data
- Similar to Part 1, read the Excel file called
favourite-food.xlsx from the data-raw/ folder,
and handle missing data and variable types.
fav_food <- read_excel(___, ___)
fav_food
Step 2: Adjust Variable Types
- Convert SES (socioeconomic status) to a factor variables with levels
in the following order:
Low, Middle,
High.
# add code here
Step 3: Save to RDS
- Write out the resulting data frame to
favourite-food.rds in the data/ folder.
# add code here
- Read
favourite-food.rds back in from the
data/ folder and observe the variable types. Are they as
you left them?
# add code here