preprocess: Create a preprocessing pipeline: a list of Preprocessor...
In rtsho/preprocessr: Functions to make your preprocessing life easier.

Typical usage will be: train <- pipe$fit_transform(train) test <- pipe$transform(test)

1	preprocess(...)

...

The preprocessor objects.

df <- data.frame(a=c(1,2,NA,3), b=c(10,20,30,NA), c=c("c1", "c2", "c3", "c4"), D=rep("d", 4), X=c(1,2,3,NA))
pipe <- preprocess(remove_constants(), impute(numerics, mean, na.rm=TRUE), impute(categoricals, most_frequent))
pipe$fit(df)
pipe$transform(df)
# or more succintly
pipe$fit_transform(df)