dplyr (version 0.7.8)

tally: Count/tally observations by group

Description

tally() is a convenient wrapper for summarise that will either call n() or sum(n) depending on whether you're tallying for the first time, or re-tallying. count() is similar but calls group_by() before and ungroup() after.

add_tally() adds a column n to a table based on the number of items within each existing group, while add_count() is a shortcut that does the grouping as well. These functions are to tally() and count() as mutate() is to summarise(): they add an additional column rather than collapsing each group.

Usage

tally(x, wt, sort = FALSE)
count(x, ..., wt = NULL, sort = FALSE)
add_tally(x, wt, sort = FALSE)
add_count(x, ..., wt = NULL, sort = FALSE)

Arguments

x

a tbl() to tally/count.

wt

(Optional) If omitted (and no variable named n exists in the data), will count the number of rows. If specified, will perform a "weighted" tally by summing the (non-missing) values of variable wt. A column named n (but not nn or nnn) will be used as weighting variable by default in tally(), but not in count(). This argument is automatically quoted and later evaluated in the context of the data frame. It supports unquoting. See vignette("programming") for an introduction to these concepts.

sort

if TRUE will sort output in descending order of n

...

Variables to group by.

Value

A tbl, grouped the same way as x.

Examples

# NOT RUN {
# tally() is short-hand for summarise()
mtcars %>% tally()
# count() is a short-hand for group_by() + tally()
mtcars %>% count(cyl)

# add_tally() is short-hand for mutate()
mtcars %>% add_tally()
# add_count() is a short-hand for group_by() + add_tally()
mtcars %>% add_count(cyl)

# count and tally are designed so that you can call
# them repeatedly, each time rolling up a level of detail
species <- starwars %>% count(species, homeworld, sort = TRUE)
species
species %>% count(species, sort = TRUE)

# add_count() is useful for groupwise filtering
# e.g.: show only species that have a single member
starwars %>%
  add_count(species) %>%
  filter(n == 1)
# }