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How to deal with error “undefined columns selected” while subsetting data in R?
When we do subsetting with the help of single square brackets we need to be careful about putting the commas at appropriate places. If we want to subset rows using the columns then comma needs to be placed before the condition. The “undefined columns selected” error occurs when we do not specify any comma. Check out the examples to understand how it works.
Consider the below data frame −
Example
x1<-rpois(20,5) x2<-rpois(20,2) df1<-data.frame(x1,x2) df1
Output
x1 x2 1 7 0 2 6 4 3 5 3 4 6 1 5 3 0 6 4 1 7 6 1 8 5 1 9 7 3 10 4 2 11 6 3 12 9 2 13 5 2 14 0 0 15 7 4 16 7 3 17 6 2 18 6 3 19 4 3 20 3 3
df1[which(x1>5)]
Error in `[.data.frame`(df1, which(x1 > 5)) : undefined columns selected
Here error occurs because comma is not used for rows inside square brackets.
Subsetting df1 based on x1 values that are greater than 5 −
Example
df1[which(x1>5),]
Output
x1 x2 1 7 0 2 6 4 4 6 1 7 6 1 9 7 3 11 6 3 12 9 2 15 7 4 16 7 3 17 6 2 18 6 3
Example
y1<-rnorm(20) y2<-rnorm(20) y3<-rnorm(20) y4<-rnorm(20) df2<-data.frame(y1,y2,y3,y4) df2
Output
y1 y2 y3 y4 1 -1.409601559 -0.40597308 -0.64615777 -1.22078887 2 0.266717714 -0.57865012 0.76654025 -1.76430465 3 -0.064943594 -1.82008803 -1.10213671 -1.40020872 4 0.809783619 -0.08933758 -0.20752297 -1.11327480 5 -0.034361207 -1.45135447 -1.16066436 0.01539031 6 -0.082024227 -1.96856577 -0.09511484 0.77846417 7 0.259362498 -0.09326561 -0.40534748 0.39772236 8 1.116127337 0.80943746 -1.01315198 -0.60320454 9 0.236156881 0.48847386 -0.72174393 -0.29582895 10 1.762595310 -0.54977615 -0.90530123 0.65145594 11 -0.321092438 0.63080804 -0.76475103 -0.30353104 12 0.020150610 1.59757420 -0.75559972 -1.96075329 13 0.164084351 -0.11924416 -0.72052393 0.14890162 14 0.658193888 -1.32640467 -0.06000406 -0.89518512 15 1.230021633 -0.73053679 2.28237747 0.24679498 16 -0.530892825 -0.69954922 -0.98488545 0.37360026 17 0.563701048 0.67395747 -0.38809559 3.50620870 18 0.001154061 -0.19090813 0.49855009 0.56542930 19 1.821508804 -0.42088642 0.75174472 -0.93212634 20 -0.118279565 1.16474884 -0.60869426 0.95720193
Subsetting df2 based on y2 values that are less than 0.5 −
Example
df2[which(y2<0.5),]
Output
y1 y2 y3 y4 1 -1.409601559 -0.40597308 -0.64615777 -1.22078887 2 0.266717714 -0.57865012 0.76654025 -1.76430465 3 -0.064943594 -1.82008803 -1.10213671 -1.40020872 4 0.809783619 -0.08933758 -0.20752297 -1.11327480 5 -0.034361207 -1.45135447 -1.16066436 0.01539031 6 -0.082024227 -1.96856577 -0.09511484 0.77846417 7 0.259362498 -0.09326561 -0.40534748 0.39772236 9 0.236156881 0.48847386 -0.72174393 -0.29582895 10 1.762595310 -0.54977615 -0.90530123 0.65145594 13 0.164084351 -0.11924416 -0.72052393 0.14890162 14 0.658193888 -1.32640467 -0.06000406 -0.89518512 15 1.230021633 -0.73053679 2.28237747 0.24679498 16 -0.530892825 -0.69954922 -0.98488545 0.37360026 18 0.001154061 -0.19090813 0.49855009 0.56542930 19 1.821508804 -0.42088642 0.75174472 -0.93212634
Updated on: 11-Feb-2021
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