This package makes it easy to to calculate entropy-based segregation indices, such as the Mutual Information Index (M) and Theil’s Information Index (H). It also implements several methods to decompose the difference between two M indices.
Tidylog provides feedback about basic data manipulations when using dplyr. This is inspired by other statistical software, such as Stata, which will give better feedback than R in many situations. Once enabled, tidylog will let you know how many rows you removed when filtering…
filtered <- filter(mtcars, cyl == 4) #> filter: removed 21 out of 32 rows (66%)
… or how many cases you recoded:
recoded <- mutate(mtcars, am = recode(am, `0 `= 2)) #> mutate: changed 19 values (59%) of 'am' (0 new NA)