Modeling on nested data frames

You'll be working on the US Army ANSUR II body measurement dataset, which has been pre-loaded as ansur_df. The goal is to nest the data for both sexes so that you can simultaneously train two linear models, one for each sex. These models will derive a person's weight from their stature (height) and waist circumference. You'll then unnest the data to inspect the model's statistics produced by the glance() function from the broom package.

The dplyr, broom, and purrr packages have been pre-loaded for you.

Side note: In the provided code, the purrr package's map() function applies functions on each nested data frame. Check out this package if you like using functions inside pipes!

Deze oefening maakt deel uit van de cursus

Reshaping Data with tidyr

Cursus bekijken

Oefeninstructies

Group the data by sex.
Nest the data.
Unnest the glanced column.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

ansur_df %>%
  # Group the data by sex
  ___ %>% 
  # Nest the data
  ___ %>% 
  mutate(
    fit = map(data, function(df) lm(weight_kg ~ waist_circum_m + stature_m, data = df)),
    glanced = map(fit, glance)
  ) %>% 
  # Unnest the glanced column
  ___

Code bewerken en uitvoeren