Apply bestNormalize Transformation to Variables in a Dataset and Update Dataset Accordingly

The transform_and_update function takes a dataset and a vector of variable names, applies the bestNormalize function to each variable, creates transformed versions of the variables when necessary, and updates the dataset and the variable list accordingly. It returns a list containing the updated dataset and the updated variable list.

Usage

get_transformation(data, var_list, seed = 100)

Arguments

data: A dataframe to which the bestNormalize function should be applied.
var_list: A character vector of variable names.
seed: A single value, interpreted as an integer, to set the random seed for reproducibility.

Value

A list with two elements: data containing the updated dataframe and var_list containing the updated variable list.

Examples

if (FALSE) {
# Generate some data
df <- data.frame(
  daily_sat_aut = rnorm(100),
  daily_fru_aut = rnorm(100),
  daily_sat_rel = rnorm(100),
  daily_fru_rel = rnorm(100)
)

# Apply the `bestNormalize` function and update dataset
result <- transform_and_update(df, var_list = c("daily_sat_aut", "daily_fru_aut", "daily_sat_rel", "daily_fru_rel"))
updated_df <- result$data
updated_var_list <- result$var_list
}