Replace NA with Zero in dplyr without using list()

Question

In dplyr I can replace NA with 0 using the following code. The issue is this inserts a list into my data frame which screws up further analysis down the line. I don't even understand lists or atomic vectors or any of that at this point. I just want to pick certain columns, and replace all occurrences of NA with zero. And maintain the columns integer status.

library(dplyr)
df <- tibble(x = c(1, 2, NA), y = c("a", NA, "b"), z = list(1:5, NULL, 10:20))
df
df %>% replace_na(list(x = 0, y = "unknown"))

That works but transforms the column into a list. How do I do it without transforming the column into a list?

And here's how to do it in base R. But not sure how to work this into a mutate statement:

df$x[is.na(df$x)] <- 0

score 100 · Answer 1 · answered Mar 31 '20 at 00:53

100

To replace all NAs in a dataframe use

df %>% replace(is.na(.), 0)

answered Mar 31 '20 at 00:53

Oliver Oliver

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worked great for me in a dplyr pipe. Thanks! – Jens Feb 03 '21 at 13:07
This is quite a nice solution. – Jae Nov 01 '21 at 22:15

score 42 · Answer 2 · edited Dec 12 '19 at 15:47

42

dt  <- mutate(dt, x = ifelse(is.na(x), 0, x))

edited Dec 12 '19 at 15:47

fdetsch

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answered Apr 20 '18 at 18:19

NT_

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score 26 · Accepted Answer · answered Apr 20 '18 at 18:20

What version of dplyr are you using? It might be an old one. The replace_na function now seems to be in tidyr. This works

library(tidyr)
df <- tibble::tibble(x = c(1, 2, NA), y = c("a", NA, "b"), z = list(1:5, NULL, 10:20))
df %>% replace_na(list(x = 0, y = "unknown")) %>% str()
# Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 3 obs. of  3 variables:
#  $ x: num  1 2 0
#  $ y: chr  "a" "unknown" "b"
#  $ z:List of 3
#   ..$ : int  1 2 3 4 5
#   ..$ : NULL
#   ..$ : int  10 11 12 13 14 15 16 17 18 19 ...

We can see the NA values have been replaced and the columns x and y are still atomic vectors. Tested with tidyr_0.7.2.

If x is kept in a variable, e.g. col_name, how should the last command be modified? — George Dontas, Jan 13 '22 at 08:13

score 0 · Answer 4 · answered Jun 12 '20 at 08:57

For the case of .xlsx, I placed an answer here.

#install.packages("xlsx")
library(xlsx)
extracted_df <- read.xlsx("test.xlsx", sheetName='Sheet1', stringsAsFactors=FALSE)
# Replace all NAs in a data frame with "G" character
extracted_df[is.na(extracted_df)] <- "G"

Replace NA with Zero in dplyr without using list()

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