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How to use column index instead of column name while using group_by of dplyr in R?
When we use group_by function of dplyr package, we need to pass the column name(s) that are categorical in nature. If we want to use the index of the same column(s) then group_by_at function needs to be used, where we can pass the column index as the argument.
Example1
Consider the below data frame −
x1<−sample(LETTERS[1:4],20,replace=TRUE) x2<−rpois(20,2) df1<−data.frame(x1,x2) df1
Output
x1 x2 1 D 4 2 D 5 3 B 2 4 D 3 5 C 1 6 C 3 7 D 1 8 D 3 9 B 3 10 B 2 11 C 0 12 C 1 13 A 2 14 B 2 15 B 2 16 C 4 17 D 2 18 A 0 19 D 0 20 B 2
Loading dplyr package and using column index instead of column name −
Example
library(dplyr) df1%>%group_by_at(1)%>%summarise(n=n()) `summarise()` ungrouping output (override with `.groups` argument)
Output
# A tibble: 4 x 2 x1 n < chr> <int> 1 A 2 2 B 6 3 C 5 4 D 7
Example2
y1<−sample(c("Male","Female"),20,replace=TRUE)
y2<−sample(21:50,20)
df2<−data.frame(y1,y2)
df2Output
y1 y2 1 Female 29 2 Male 43 3 Female 34 4 Male 49 5 Male 28 6 Female 23 7 Female 27 8 Female 31 9 Female 36 10 Female 41 11 Male 25 12 Female 24 13 Male 30 14 Female 22 15 Female 37 16 Male 42 17 Female 47 18 Male 35 19 Female 32 20 Female 21
Using column index instead of column name to summarise y1 −
Example
df2%>%group_by_at(1)%>%summarise(n=n()) `summarise()` ungrouping output (override with `.groups` argument)
Output
# A tibble: 2 x 2 y1 n <chr> <int> 1 Female 13 2 Male 7
Updated on: 09-Feb-2021
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