将NA替换为“”，但仅限于字符列

I have a large dataset with ~200 columns of various types. I need to replace NA values with "", but only in character columns.

我有一个包含各种类型约200列的大型数据集。我需要用“”替换NA值,但只能在字符列中。

Using the dummy data table

使用虚拟数据表

DT <- data.table(x = c(1, NA, 2),
                y = c("a", "b", NA))

> DT
    x    y
1:  1    a
2: NA    b
3:  2 <NA>

> str(DT)
Classes ‘data.table’ and 'data.frame':  3 obs. of  2 variables:
 $ x: num  1 NA 2
 $ y: chr  "a" "b" NA

I have tried the following for-loop with a condition, but it doesn't work.

我尝试了以下for循环的条件,但它不起作用。

for (i in names(DT)) {
  if (class(DT$i) == "character") {
    DT[is.na(i), i := ""]
  }
}

The loop runs with no errors, but doesn't change the DT.

循环运行没有错误,但不会更改DT。

The expected output I am looking for is this:

我正在寻找的预期输出是这样的:

    x y
1:  1 a
2: NA b
3:  2

The solution doesn't necessarily have to involve a loop, but I couldn't think of one.

解决方案不一定涉及循环,但我想不到一个。

2 个解决方案

#1

DT[,  lapply(.SD, function(x){if(is.character(x)) x[is.na(x)] <-  ' '; x})]

Or, if you don't like typing function(x)

或者,如果你不喜欢打字功能(x)

library(purrr)
DT[,  map(.SD, ~{if(is.character(.x)) .x[is.na(.x)] <-  ' '; .x})]

To replace

DT[, names(DT) :=  map(.SD, ~{if(is.character(.x)) .x[is.na(.x)] <-  ' '; .x})]

#2

One option if you don't mind using dplyr:

如果您不介意使用dplyr,可以选择一种方法:

na_to_space <- function(x) ifelse(is.na(x)," ",x)
> DT %>% mutate_if(.predicate = is.character,.funs = na_to_space)
   x y
1  1 a
2 NA b
3  2

#1

DT[,  lapply(.SD, function(x){if(is.character(x)) x[is.na(x)] <-  ' '; x})]