Reputation: 165
I have a dataframe that looks like this:
Dog Breed Dog.Distraction Resource.Guarding
1 Max BL N/A 1
2 Rover YL 1 N/A
3 Tina GR 1 N/A
I want a new dataframe that looks like:
Dog. Distraction Resource.Guarding
Count 2 1
What's the best way to do this? I can use sum() to find each individual column, but not sure how to convert to new df. Alternatively, I'm also ok with:
Count
Dog.Distraction 2
Resource.Guarding 1
Thank you!
Upvotes: 2
Views: 27
Reputation: 887221
We can use colSums
assuming the N/A
is NA
out <- colSums(df1[c('Dog.Distraction', 'Resource.Guarding')], na.rm = TRUE)
If we need to change the names
names(out) <- c("V1", "V2")
The output of colSums
is a named vector
Upvotes: 1