Correct syntax for mutate_if

Question

I would like to replace NA values with zeros via mutate_if in dplyr. The syntax below:

set.seed(1)
mtcars[sample(1:dim(mtcars)[1], 5),
       sample(1:dim(mtcars)[2], 5)] <-  NA

require(dplyr)

mtcars %>% 
    mutate_if(is.na,0)

mtcars %>% 
    mutate_if(is.na, funs(. = 0))

Returns error:

Error in vapply(tbl, p, logical(1), ...) : values must be length 1, but FUN(X[[1]]) result is length 32

What's the correct syntax for this operation?

for this particular task, you might also consider the simpler `tidyr::replace_na` rather than the more generic `mutate_if` approaches — cboettig, Jun 06 '18 at 03:16

yusuzech · Accepted Answer · 2020-05-19T17:58:53.170

I learned this trick from the purrr tutorial, and it also works in dplyr. There are two ways to solve this problem:
First, define custom functions outside the pipe, and use it in mutate_if():

any_column_NA <- function(x){
    any(is.na(x))
}
replace_NA_0 <- function(x){
    if_else(is.na(x),0,x)
}
mtcars %>% mutate_if(any_column_NA,replace_NA_0)

Second, use the combination of ~,. or .x.( .x can be replaced with ., but not any other character or symbol):

mtcars %>% mutate_if(~ any(is.na(.x)),~ if_else(is.na(.x),0,.x))
#This also works
mtcars %>% mutate_if(~ any(is.na(.)),~ if_else(is.na(.),0,.))

In your case, you can also use mutate_all():

mtcars %>% mutate_all(~ if_else(is.na(.x),0,.x))

Using ~, we can define an anonymous function, while .x or . stands for the variable. In mutate_if() case, . or .x is each column.

Purrr Tutorial has moved to https://rstudio.com/resources/rstudioconf-2017/happy-r-users-purrr-tutorial-/ — David T, May 17 '20 at 23:20

score 53 · Answer 2 · answered Feb 05 '17 at 12:39

53

The "if" in mutate_if refers to choosing columns, not rows. Eg mutate_if(data, is.numeric, ...) means to carry out a transformation on all numeric columns in your dataset.

If you want to replace all NAs with zeros in numeric columns:

data %>% mutate_if(is.numeric, funs(ifelse(is.na(.), 0, .)))

answered Feb 05 '17 at 12:39

Hong Ooi

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5

working fine, one might use `if_else` instead to stay in the `tidyverse` and benefit for the additionnal check of the TRUE, FALSE type coherence – aurelien Oct 13 '17 at 11:40
if you want to check if it's NA or equal to "NA" in the ifelse how you caan solve this (add another condition) – Mostafa90 Sep 06 '18 at 07:34

Nettle · Answer 3 · 2021-12-28T22:29:25.887

26

mtcars %>% mutate_if(is.numeric, replace_na, 0)

or more recent syntax

mtcars %>% mutate(across(where(is.numeric),
                         replace_na, 0))

edited Dec 28 '21 at 22:29

answered Jun 17 '18 at 17:37

Nettle

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Simplicity is important. If a simple line of code can do the same thing as more complex, long code, I think it should be chosen instead. – Darius Jan 24 '20 at 23:38
This should be in the help page for `mutate_if`. Thanks for making my life easier. – Megatron Oct 14 '21 at 20:35

score 4 · Answer 4 · answered Feb 05 '17 at 14:34

4

We can use set from data.table

library(data.table)
setDT(mtcars)
for(j in seq_along(mtcars)){
  set(mtcars, i= which(is.na(mtcars[[j]])), j = j, value = 0)
 }

answered Feb 05 '17 at 14:34

akrun

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How might this be modified to only operate on numeric variables please? – Rick Pack Jan 20 '21 at 19:33
1

@RickPack. You could change the `for(j in seq_along(mtcars))` to `nm1 <- names(mtcars)[mtcars[, unlist(lapply(.SD, is.numeric))]; for(j in nm1)` – akrun Jan 20 '21 at 19:35

score 3 · Answer 5 · answered Oct 23 '18 at 12:38

3

I always struggle with replace_na function of dplyr

  replace(is.na(.),0)

this works for me for what you are trying to do.

answered Oct 23 '18 at 12:38

ok1more

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Correct syntax for mutate_if

5 Answers5

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