How to delete columns that contain ONLY NAs?
I have a data.frame containing some columns with all NA values, how can I delete them from the data.frame.
Can I use the function
na.omit(...)
specifying some additional arguments?
One way of doing it:
df[, colSums(is.na(df)) != nrow(df)]
If the count of NAs in a column is equal to the number of rows, it must be entirely NA.
Or similarly
df[colSums(!is.na(df)) > 0]
It seeems like you want to remove ONLY columns with ALL NA s, leaving columns with some rows that do have NA s. I would do this (but I am sure there is an efficient vectorised soution:
#set seed for reproducibility
set.seed <- 103
df <- data.frame( id = 1:10 , nas = rep( NA , 10 ) , vals = sample( c( 1:3 , NA ) , 10 , repl = TRUE ) )
df
# id nas vals
# 1 1 NA NA
# 2 2 NA 2
# 3 3 NA 1
# 4 4 NA 2
# 5 5 NA 2
# 6 6 NA 3
# 7 7 NA 2
# 8 8 NA 3
# 9 9 NA 3
# 10 10 NA 2
#Use this command to remove columns that are entirely NA values, it will elave columns where only some vlaues are NA
df[ , ! apply( df , 2 , function(x) all(is.na(x)) ) ]
# id vals
# 1 1 NA
# 2 2 2
# 3 3 1
# 4 4 2
# 5 5 2
# 6 6 3
# 7 7 2
# 8 8 3
# 9 9 3
# 10 10 2
If you find yourself in the situation where you want to remove columns that have any NA values you can simply change the all command above to any .
这是一个dplyr解决方案：
df %>% select_if(~sum(!is.na(.)) > 0)
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