Hi,
Here is a way of testing the different columns for missing or 0 values
#Dummy data
myData = data.frame(x = 1:10,
y = c(1,5,0.2,0,0,8,NA,5,NA,6.3),
z = c(1,NA,0.2,7,0,8,4.3,5,0,6.3))
#Number of values in columns that are missing or 0
nMissing = apply(myData, 2, function(x){
sum(is.na(x) | x == 0)
})
nMissing
#> x y z
#> 0 4 3
#Number of 'correct' values in each column
nrow(myData) - nMissing
#> x y z
#> 10 6 7
Created on 2021-08-26 by the reprex package (v2.0.1)
The apply
function runs a function over each column (option 2 as second argument), in this case a check of NA or 0
Since I could not work with your data or code, I came up with a dummy example. Next time consider creating a reprex. A reprex consists of the minimal code and data needed to recreate the issue/question you're having. You can find instructions how to build and share one here:
Hope this helps,
PJ