Replace NA with Zero in dplyr without using list()

问题

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

回答1:

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.

回答2:

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

来源：https://stackoverflow.com/questions/49947592/replace-na-with-zero-in-dplyr-without-using-list