Using if else on a dataframe across multiple columns

Question

I have a large dataset of samples with descriptors of whether the sample is viable - it looks (kind of) like this, where \'desc\' is the description column and \'blank\' ind

Answer 1

Here is an option using set from data.table. It should be faster as the overhead of [.data.table is avoided. We convert the 'data.frame' to 'data.table' (setDT(df1)), loop through the column names of 'df1' (excluding the 'desc' column'), assign the elements to "NA" where the logical condition is 'i' is met.

library(data.table)
setDT(df1)
for(j in names(df1)[-1]){
   set(df1, i= which(df1[["desc"]]=="blank"), j= j, value= NA)
}
df1
#      desc        x        y        z
# 1:  blank       NA       NA       NA
# 2:  blank       NA       NA       NA
# 3: sample 4.322014 4.798248 4.995959
# 4: sample 3.997565 5.975604 7.160871
# 5:  blank       NA       NA       NA
# 6:  blank       NA       NA       NA
# 7:  blank       NA       NA       NA
# 8: sample 4.382937 5.926217 5.203737
# 9: sample 4.976908 3.079191 4.614121
#10:  blank       NA       NA       NA

Or another option (based on @dww's comment)

setDT(df1, key = "desc")["blank", names(df1)[-1] := NA][]