In hope-data-science/tidyfst: Tidy Verbs for Fast Data Manipulation

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

This vignette displays how to use nesting in tidyfst. It has referred to tidyrs vignette in https://tidyr.tidyverse.org/articles/nest.html. Now fist, we nest the "mtcars" data.frame by "cyl" column.

library(tidyfst)

# nest by "cyl" column
mtcars_nested <- mtcars %>% 
  nest_dt(cyl) # you can use "cyl" too, very flexible

# inspect the output data.table
mtcars_nested

Now, we want to do a regression within the nested group "cyl". We'll use the famous lapply to complete this:

mtcars_nested2 <- mtcars_nested %>% 
  mutate_dt(model = lapply(ndt,function(df) lm(mpg ~ wt, data = df)))

mtcars_nested2

We could see that the model is stored in the column "model". Now, we try to get the fitted value in the model.

mtcars_nested3 <- mtcars_nested2 %>% 
  mutate_dt(model_predict = lapply(model, predict))
mtcars_nested3$model_predict

We could find that the "model_predict" is a list of numeric vectors. Let's try to unnest the target column "model_predict".

mtcars_nested3 %>% unnest_dt(model_predict)

This process would remove all the other list column automatically. For instance, in our case, the column "ndt" is removed.

hope-data-science/tidyfst documentation built on Sept. 23, 2024, 8:05 p.m.