In dplyr
, how do you perform rowwise summation over selected columns (using column index)?
This doesn't work
> iris %>% mutate(sum=sum(.[1:4])) %>% head
Sepal.Length Sepal.Width Petal.Length Petal.Width Species sum
1 5.1 3.5 1.4 0.2 setosa 2078.7
2 4.9 3.0 1.4 0.2 setosa 2078.7
3 4.7 3.2 1.3 0.2 setosa 2078.7
4 4.6 3.1 1.5 0.2 setosa 2078.7
5 5.0 3.6 1.4 0.2 setosa 2078.7
6 5.4 3.9 1.7 0.4 setosa 2078.7
I can do the following, but it's not beautiful
> iris %>% mutate(index=1:n()) %>%
gather("param", "value", 1:4) %>%
group_by(index) %>%
mutate(sum=sum(value)) %>%
spread(param, value) %>% select(-index)
Source: local data frame [150 x 6]
Species sum Sepal.Length Sepal.Width Petal.Length Petal.Width
1 setosa 10.2 5.1 3.5 1.4 0.2
2 setosa 9.5 4.9 3.0 1.4 0.2
3 setosa 9.4 4.7 3.2 1.3 0.2
4 setosa 9.4 4.6 3.1 1.5 0.2
5 setosa 10.2 5.0 3.6 1.4 0.2
6 setosa 11.4 5.4 3.9 1.7 0.4
7 setosa 9.7 4.6 3.4 1.4 0.3
8 setosa 10.1 5.0 3.4 1.5 0.2
9 setosa 8.9 4.4 2.9 1.4 0.2
10 setosa 9.6 4.9 3.1 1.5 0.1
.. ... ... ... ... ... ...
Is there more syntactically nicer way to achieve this?
EDIT: It's different from other questions, because I want to do rowwise operation on the columns selected by using column indices"
As already said in the comment, you can accomplish your task with:
iris %>% mutate(sum=Reduce("+",.[1:4]))
In this case also the base rowSums
works:
iris$sum<-rowSums(iris[,1:4])
You can (ab)use base R's subset
, which allows selection of columns by number:
iris %>% subset(select=1:4) %>% mutate(sum=rowSums(.))
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