I have a data frame like this
> df
Source: local data frame [4 x 4]
a x y z
1 name1 1 1 1
2 name2 1 1 1
3 name3 1 1 1
4 name4 1 1 1
W
If you want to keep non-numeric columns in the result, you can do this:
dat %>% mutate(total=rowSums(.[, sapply(., is.numeric)]))
UPDATE: Now that dplyr
has scoped versions of its standard verbs, here's another option:
dat %>% mutate(total=rowSums(select_if(., is.numeric)))
UPDATE 2: With dplyr 1.0, the approaches above will still work, but you can also do row sums by combining rowwise
and c_across
:
iris %>%
rowwise %>%
mutate(row.sum = sum(c_across(where(is.numeric))))