Select columns that have more than 1 unique value [duplicate]

Question

I currently have the following dataframe:

datnotformeanfill<-
  data.frame(b8=c(1,2,2,2,1,1),b7=rep(1,6),
             b6=c(6,2,3,3,6,3),b5=c(6,3,3,3,4,3),
             b4=c(rep(6,5),1),b3=rep(0,6),
             b2=rep(1,6),b1=c(2,2,2,2,1,1))

> datnotformeanfill
  b8 b7 b6 b5 b4 b3 b2 b1
1  1  1  6  6  6  0  1  2
2  2  1  2  3  6  0  1  2
3  2  1  3  3  6  0  1  2
4  2  1  3  3  6  0  1  2
5  1  1  6  4  6  0  1  1
6  1  1  3  3  1  0  1  1

I am trying to use a combination of the which and unique functions to return only the columns which have more than 1 unique value, but am not completely certain how to use these (or perhaps some other function(s)) to return the columns. Any help would be appreciated. Thank you!

Answer 1

We can use Filter with function f = var. It will check the variance for each column. If the column have only a single unique value, the variance will be '0'. This will be converted back to logical 'FALSE/TRUE' and used for subsetting the dataset.

 Filter(var, datnotformeanfill)
 #    b8 b6 b5 b4 b1
 #  1  1  6  6  6  2
 #  2  2  2  3  6  2
 #  3  2  3  3  6  2
 #  4  2  3  3  6  2
 #  5  1  6  4  6  1
 #  6  1  3  3  1  1

Or another option is looping through the columns with sapply and check the condition whether the length of unique elements are greater than 1. This returns a logical 'TRUE/FALSE' vector that can be used for subsetting as well.

datnotformeanfill[sapply(datnotformeanfill, function(x) length(unique(x))>1)]