Reputation: 1948
I have a data frame and want to count the number of zeros in each row using dplyr's rowwise. What am I doing wrong?
dt2 = data.frame(A = c(8, 6), B = c(0, 0), C = c(0, 5))
dt2
zerocount <- function(x) {sum(x == 0)}
library(dplyr)
dt2 %>% rowwise() %>% mutate(nr_of_0s = zerocount(A, B, C))
The code above works if I replace zerocount(A, B, C) in the line above with, for example, max(A, B, C). What is wrong? Thank you!
Upvotes: 4
Views: 4564
Reputation: 8107
Another method without using rowwise()
:
mutate(dt2, zero_count = pmap_int(dt2, function(...) sum(c(...) == 0)))
> A B C zero_count
> 1 8 0 0 2
> 2 6 0 5 1
pmap()
is a purrr
function that takes takes elements from a list (which in this case is the data frame) and applies a function. In this case, I'm just applying your function on the fly. By default, pmap()
returns a list, but using the _int
suffix makes it return an integer vector.
Upvotes: 2
Reputation: 3321
A logical test for the presence of zeros would look like:
dt2==0
A B C
[1,] FALSE TRUE TRUE
[2,] FALSE TRUE FALSE
Sum the number of Trues by row
rowSums(dt2==0)
[1] 2 1
With this in mind, here's a tidyverse solution:
dt2 %>%
mutate(zero.count = rowSums(.==0) ) #<The dot is shorthand for dt2
A B C zero.count
1 8 0 0 2
2 6 0 5 1
Upvotes: 2
Reputation: 376
I don't think your problem is with rowwise. The way your function is written, it's expecting a single object. Try adding a c():
dt2 %>% rowwise() %>% mutate(nr_of_0s = zerocount(c(A, B, C)))
Note that, if you aren't committed to using your own function, you can skip rowwise entirely, as Nettle also notes. rowSums
already treats data frames in a rowwise fashion, which is why this works:
dt2 %>% mutate(nr_of_0s = rowSums(. == 0))
Upvotes: 4