What is the most efficient way to remove empty columns in a datatable in R

Question

I have some import issues with a file, that create an empty column at the end such as :

library(data.table)
library(tidyverse)
MWE <- data.table(var1=c(1,2),var2=c(3,4),var3=c(NA,NA))

Now I can remove it easily as I know the empty column is the last one :

MWE2 <- MWE[,c(length(MWE)):=NULL]

But I wondered how I would do if I just wanted to remove a random empty column without knowing its number. A quick search here and on the datatable page gave me a lot of examples on how to :

• remove empty lines in datatables, through na.omit
• remove empty columns in a dataframe, for instance here

But I did not find solutions to remove empty columns in datatables. What are the options and which is the fastest ?

Answer 1

We could check if all values are NA in a column, get the column name and assign those to NULL

nm1 <- MWE[, names(which(sapply(.SD, function(x) all(is.na(x)))))] 
# or
# nm1 <- MWE[, names(which(!colSums(!is.na(.SD))))]
MWE[, (nm1) := NULL]

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Or with Filter

MWE[, Filter(function(x) any(!is.na(x)), .SD)]

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Or using select

library(dplyr)
MWE %>%
     select(where(~ any(!is.na(.))))