Exercise 2_1_1: Selecting & renaming variables

As in the presentation, we will use stackoverflow_survey_single_response.csv. You should (have) download(ed) the dataset or find it in a folder called data within the folder containing the materials for this workshop.

library (tidyverse)
library (haven)
library(sjlabelled)
library(readr)


stackoverflow_survey_single_response <- read_csv("./data/stackoverflow_survey_single_response.csv")

2

Using base R, create a new object called user_background that contains all variables that assess the respondent characteristics (like age, education, years of coding experience).

Clues

The first variable we want to select for our subset is named main_branch, and the last one is years_code_pro. They appear consecutively in the data set. Remember that there are two options for selecting columns in base R: One is subsetting using [ ], the other is the subset() function.

solution

# Option 1
tuesdata_person <- stackoverflow_survey_single_response[, c("main_branch",
                               "age",
                               "remote_work",
                               "ed_level",
                               "years_code",
                               "years_code_pro")]
# Option 2
tuesdata_person  <- subset(stackoverflow_survey_single_response, TRUE, select = c(main_branch:years_code_pro))

4

Again, using a function from the tidyverse package dplyr, select only the character variables from the stackoverflow_survey_single_response data and assign them to an object named tuesdata_char.

Clues

You need to use the selection helper where() for this task.

solution

tuesdata_char <-stackoverflow_survey_single_response %>% 
  select(where(is.character))

5

After creating subsets of variables, let’s now rename those variables using dplyr functions again for the tuesdata_person object in one step.

Clues

You can also rename variables within the select() command.

solution

tuesdata_person <- stackoverflow_survey_single_response %>% 
  select(motivation = main_branch,
         age_group = age,
         work_mode = remote_work,
         edu_level = ed_level,
         yrs_experience  = years_code,
         yrs_professional = years_code_pro)