Alternative to Sapply in dplyr

user_4930357 0
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I want to know how we can write similar to sapply in dplyr. Here I am calculating no. of distinct values. I have similar multiple sapply statements so I thought to write using mutate in dplyr.

distinctValues <- sapply(iris, function(var) dplyr::n_distinct(var))
dplyr r
4 Answers

Update: for different names you can use .names = "{.col}.new{.fn}"

iris %>% 
  summarize(across(everything(), n_distinct, .names = "{.col}.new{.fn}"))

We can use summarize with across

library(dplyr)
iris %>% 
  summarize(across(everything(), n_distinct))

Output:

  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1           35          23           43          22       3
user_133216470

In base R, we can do

sapply(iris, function(var) length(unique(var)))
user_37322710

You can also use the following solution:

library(purrr)

iris %>%
  map_dbl(~ n_distinct(.x))

Sepal.Length  Sepal.Width Petal.Length  Petal.Width      Species 
          35           23           43           22            3
user_143145200

A data.table option using uniqueN

> as.data.table(iris)[, sapply(.SD, uniqueN)]
Sepal.Length  Sepal.Width Petal.Length  Petal.Width      Species 
          35           23           43           22            3
user_121587570
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