First, I had a list that including several dataframes like this:

list:

$dataframes1

A	B
1	2
NA	3
1	2
NA	NA
1	NA
NA	NA
1	2
NA	3
1	2
1	NA

$dataframes2

A	B
1	2
1	3
1	2
1	3
7	2
1	3
1	2
5	3
7	2
1	3

$dataframes3

A	B
NA	2
1	3
NA	2
1	3
NA	2
1	3
NA	2
1	3
NA	2
1	3

$dataframes4

A	B
1	2
1	3
3	2
1	3
3	4
1	3
5	5
5	3
1	NA
1	3

They all have the same number of rows and variables (i.e., A and B), and there are some NAs in the dataset, If a variable in the dataframe contain > 3NAs, then the corresponding column will return a NA vector, otherwise remains the same:

e.g.

$dataframes3

A	B
NA	2
NA	3
NA	2
NA	3
NA	2
NA	3
NA	2
NA	3
NA	2
NA	3

My expected output:

list:

$dataframes1

A	B
NA	NA
NA	NA
NA	NA
NA	NA
NA	NA
NA	NA
NA	NA
NA	NA
NA	NA
NA	NA

$dataframes2

A	B
1	2
1	3
1	2
1	3
7	2
1	3
1	2
5	3
7	2
1	3

$dataframes3

A	B
NA	2
NA	3
NA	2
NA	3
NA	2
NA	3
NA	2
NA	3
NA	2
NA	3

$dataframes4

A	B
1	2
1	3
3	2
1	3
3	4
1	3
5	5
5	3
1	NA
1	3

Is there any way to convert the dataframes in the list without using >2 for loop? I used 3 for loops to convert and the running speed is very slow... May be using lapply to each dataframe is a good solution? But the code will become difficult to read and debug?

CodePudding user response：

This should do the trick:

library(purrr)
library(dplyr)

map(dataframes, ~ mutate(
  .x, 
  across(
    everything(),
    ifelse(sum(is.na(.x)) <= 3, .x, NA)
  )
)