[英]Changing NA to “N” in selected factor columns in R data frame
I have a the following data frame with factor columns. 我有一个带有因子列的以下数据框。
set.seed(1234)
df <- data.frame(a=sample(c("1","2",NA), 10, replace=T),
b=sample(c("1","2",NA), 10, replace=T),
c=sample(c("1","2","3",NA), 10, replace=T))
which is 这是
df
a b c
1 1 <NA> 2
2 2 2 2
3 2 1 1
4 2 <NA> 1
5 <NA> 1 1
6 2 <NA> <NA>
7 1 1 3
8 1 1 <NA>
9 2 1 <NA>
10 2 1 1
Now, I want to create a new level "N" for selected columns and convert all NA in those column to "N". 现在,我想为所选列创建一个新级别“ N”,并将这些列中的所有NA都转换为“ N”。 I make a vector of selected column names by
我将所选列名的向量
selected <- c("b", "c")
and then try to use apply
in the following way 然后尝试通过以下方式使用
apply
apply(df, 2, function(x) {(if x %in% selected) x <- factor(x, levels=c(levels(x), 'N'))})
But it gives error: 但是它给出了错误:
Error: unexpected symbol in "apply(df, 2, function(x) {(if x"
In my original data, I have lots of columns. 在我的原始数据中,我有很多列。 So I want to avoid doing it column by column.
因此,我想避免逐列进行。
The 'levels' of the 'selected' columns before the operation is: 操作前“选定”列的“级别”为:
lapply(df[selected], levels)
#$b
#[1] "1" "2"
#$c
#[1] "1" "2" "3"
We can 'loop' over the columns in the 'selected' with lapply
, include 'N' as one more level in each column, and replace
the 'NA' values with 'N'. 我们可以使用
lapply
在“ selected”中的列上“循环”,在每列中lapply
“ N”个级别,并用“ N” replace
“ NA”值。
df[selected] <- lapply(df[selected], function(x) {
levels(x) <- c(levels(x), 'N')
replace(x, which(is.na(x)), 'N')
})
Or another option is recode
from car
, where we can directly change 'NA' to 'N'. 另一个选择是从
car
recode
,我们可以直接将'NA'更改为'N'。 It will automatically update the levels. 它将自动更新级别。
library(car)
df[selected] <- lapply(df[selected], recode, "NA='N'")
lapply(df[selected], levels)
#$b
#[1] "1" "2" "N"
#$c
#[1] "1" "2" "3" "N"
Another useful function is addNA
if we want to add "NA" one of the levels 如果我们要添加“ NA”级别之一,则另一个有用的功能是
addNA
df[selected] <- lapply(df[selected], addNA)
NOTE: The output of apply
on a non-numeric column will be 'character' class. 注意:在非数字列上
apply
的输出将是'character'类。 I guess that is not you wanted. 我想那不是你想要的。
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