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!
Este ejercicio forma parte del curso
Reshaping Data with tidyr
Instrucciones del ejercicio
- Group the data by
sex. - Nest the data.
- Unnest the
glancedcolumn.
Ejercicio interactivo práctico
Prueba este ejercicio completando el código de muestra.
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
___