Compute on a data frame a row-at-a-time. This is most useful when a vectorised function doesn't exist. Only mutate and summarise are supported so far.
rowwise_mutate(.data, ...)
rowwise_summarise(.data, ...)A data.table
# without rowwise
df <- data.table(x = 1:2, y = 3:4, z = 4:5)
df %>% mutate(m = mean(c(x, y, z)))
#> x y z m
#> <int> <int> <int> <num>
#> 1: 1 3 4 3.166667
#> 2: 2 4 5 3.166667
# with rowwise
df <- data.table(x = 1:2, y = 3:4, z = 4:5)
df %>% rowwise_mutate(m = mean(c(x, y, z)))
#> x y z m
#> <int> <int> <int> <num>
#> 1: 1 3 4 2.666667
#> 2: 2 4 5 3.666667
# # rowwise is also useful when doing simulations
params = fread(" sim n mean sd
1 1 1 1
2 2 2 4
3 3 -1 2")
params %>%
rowwise_summarise(sim,z = rnorm(n,mean,sd))
#> sim z
#> <int> <num>
#> 1: 1 1.9353632
#> 2: 2 2.7059544
#> 3: 2 2.9747419
#> 4: 3 2.2470978
#> 5: 3 -0.7759238
#> 6: 3 -1.2679940