dplyr: how to reference columns by column index rather than column name using mutate?
Using dplyr, you can do something like this:
iris %>% head %>% mutate(sum=Sepal.Length + Sepal.Width)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species sum
1 5.1 3.5 1.4 0.2 setosa 8.6
2 4.9 3.0 1.4 0.2 setosa 7.9
3 4.7 3.2 1.3 0.2 setosa 7.9
4 4.6 3.1 1.5 0.2 setosa 7.7
5 5.0 3.6 1.4 0.2 setosa 8.6
6 5.4 3.9 1.7 0.4 setosa 9.3
But above, I referenced the columns by their column names. How can I use 1 and 2 , which are the column indices to achieve the same result?
Here I have the following, but I feel it's not as elegant.
iris %>% head %>% mutate(sum=apply(select(.,1,2),1,sum))
Sepal.Length Sepal.Width Petal.Length Petal.Width Species sum
1 5.1 3.5 1.4 0.2 setosa 8.6
2 4.9 3.0 1.4 0.2 setosa 7.9
3 4.7 3.2 1.3 0.2 setosa 7.9
4 4.6 3.1 1.5 0.2 setosa 7.7
5 5.0 3.6 1.4 0.2 setosa 8.6
6 5.4 3.9 1.7 0.4 setosa 9.3
Solution 1:
You can try:
iris %>% head %>% mutate(sum = .[[1]] + .[[2]])
Sepal.Length Sepal.Width Petal.Length Petal.Width Species sum
1 5.1 3.5 1.4 0.2 setosa 8.6
2 4.9 3.0 1.4 0.2 setosa 7.9
3 4.7 3.2 1.3 0.2 setosa 7.9
4 4.6 3.1 1.5 0.2 setosa 7.7
5 5.0 3.6 1.4 0.2 setosa 8.6
6 5.4 3.9 1.7 0.4 setosa 9.3
Solution 2:
I'm a bit late to the game, but my personal strategy in cases like this is to write my own tidyverse-compliant function that will do exactly what I want. By tidyverse-compliant, I mean that the first argument of the function is a data frame and that the output is a vector that can be added to the data frame.
sum_cols <- function(x, col1, col2){
x[[col1]] + x[[col2]]
}
iris %>%
head %>%
mutate(sum = sum_cols(x = ., col1 = 1, col2 = 2))
Solution 3:
What do you think about this version?
Inspired by @SavedByJesus's answer.
applySum <- function(df, ...) {
assertthat::assert_that(...length() > 0, msg = "one or more column indexes are required")
mutate(df, Sum = apply(as.data.frame(df[, c(...)]), 1, sum))
}
iris %>%
head(2) %>%
applySum(1, 2)
#
### output
#
Sepal.Length Sepal.Width Petal.Length Petal.Width Species Sum
1 5.1 3.5 1.4 0.2 setosa 8.6
2 4.9 3.0 1.4 0.2 setosa 7.9
#
### you can select and sum more then two columns by the same function
#
iris %>%
head(2) %>%
applySum(1, 2, 3, 4)
#
### output
#
Sepal.Length Sepal.Width Petal.Length Petal.Width Species Sum
1 5.1 3.5 1.4 0.2 setosa 10.2
2 4.9 3.0 1.4 0.2 setosa 9.5