Relative frequencies / proportions with dplyr

Question

Suppose I want to calculate the proportion of different values within each group. For example, using the mtcars data, how do I calculate the relative frequency of number of gears by am (automatic/manual) in one go with dplyr?

library(dplyr)
data(mtcars)
mtcars <- tbl_df(mtcars)

# count frequency
mtcars %>%
  group_by(am, gear) %>%
  summarise(n = n())

# am gear  n
#  0    3 15 
#  0    4  4 
#  1    4  8  
#  1    5  5 

What I would like to achieve:

am gear  n rel.freq
 0    3 15      0.7894737
 0    4  4      0.2105263
 1    4  8      0.6153846
 1    5  5      0.3846154

Answer 1

Try this:

mtcars %>%
  group_by(am, gear) %>%
  summarise(n = n()) %>%
  mutate(freq = n / sum(n))

#   am gear  n      freq
# 1  0    3 15 0.7894737
# 2  0    4  4 0.2105263
# 3  1    4  8 0.6153846
# 4  1    5  5 0.3846154

From the dplyr vignette:

When you group by multiple variables, each summary peels off one level of the grouping. That makes it easy to progressively roll-up a dataset.

Thus, after the summarise, the last grouping variable specified in group_by, 'gear', is peeled off. In the mutate step, the data is grouped by the remaining grouping variable(s), here 'am'. You may check grouping in each step with groups.

The outcome of the peeling is of course dependent of the order of the grouping variables in the group_by call. You may wish to do a subsequent group_by(am), to make your code more explicit.

For rounding and prettification, please refer to the nice answer by @Tyler Rinker.