data

In discovr: Interactive Tutorials and Data for "Discovering Statistics Using R and RStudio"

Data

To work outside of this tutorial you need to download the following data file:

• speed_date.csv
• profile_pic.csv

Set up an r rstudio() project in the way that I recommend in this video, and save the data files to the folder within your project called [data]{.alt}. Place this code in the first code chunk in your r quarto() document:

date_tib <- here::here("data/speed_date.csv") |>
  read_csv() |>
  mutate(
    strategy = as_factor(strategy) |> fct_relevel("Normal", "Hard to get"),
    looks = as_factor(looks) |> fct_relevel("Low", "Average", "High"),
    charisma = as_factor(charisma) |> fct_relevel("Low", "Average", "High"),
  )

This code reads in the data and converts the variables strategy, looks and charisma to be factors (categorical variable). It also uses fct_relevel() to set the order of the levels of each factor.

For the profile picture data use the code below. The variables rel_status and profile_pic are converted to factors and the reference category for each is set using fct_relevel():

profile_tib <- here::here("data/profile_pic.csv") |>
  read_csv() |>
  mutate(
    rel_status = as_factor(rel_status) |> fct_relevel("Single"),
    profile_pic = as_factor(profile_pic) |> fct_relevel("Alone")
  )

discovr documentation built on Feb. 5, 2026, 5:07 p.m.