Source: R/count-tally.R
tally.Rd
tally() is a convenient wrapper for summarise that will either calln() or sum(n) depending on whether you're tallyingfor the first time, or re-tallying. count() is similar but callsgroup_by() before and ungroup() after. If the data is alreadygrouped, count() adds an additional group that is removed afterwards.
add_tally() adds a column n to a table based on the numberof items within each existing group, while add_count() is a shortcut thatdoes 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.
tally(x, wt = NULL, sort = FALSE, name = "n")count(x, ..., wt = NULL, sort = FALSE, name = "n", .drop = group_by_drop_default(x))add_tally(x, wt, sort = FALSE, name = "n")add_count(x, ..., wt = NULL, sort = FALSE, name = "n")
Arguments
| x | a |
|---|---|
| wt | (Optional) If omitted (and no variable named |
| sort | if |
| name | The output column name. If omitted, it will be |
| ... | Variables to group by. |
| .drop | see |
Value
A tbl, grouped the same way as x.
Note
The column name in the returned data is given by the name argument,set to "n" by default.
If the data already has a column by that name, the output columnwill be prefixed by an extra "n" as many times as necessary.
Examples
# tally() is short-hand for summarise()mtcars %>% tally()
#> n#> 1 32
mtcars %>% group_by(cyl) %>% tally()
#> # A tibble: 3 x 2#> cyl n#> <dbl> <int>#> 1 4 11#> 2 6 7#> 3 8 14
# count() is a short-hand for group_by() + tally()mtcars %>% count(cyl)
#> # A tibble: 3 x 2#> cyl n#> <dbl> <int>#> 1 4 11#> 2 6 7#> 3 8 14
# Note that if the data is already grouped, count() adds# an additional group that is removed afterwardsmtcars %>% group_by(gear) %>% count(carb)
#> # A tibble: 11 x 3#> # Groups: gear [3]#> gear carb n#> <dbl> <dbl> <int>#> 1 3 1 3#> 2 3 2 4#> 3 3 3 3#> 4 3 4 5#> 5 4 1 4#> 6 4 2 4#> 7 4 4 4#> 8 5 2 2#> 9 5 4 1#> 10 5 6 1#> 11 5 8 1
# add_tally() is short-hand for mutate()mtcars %>% add_tally()
#> # A tibble: 32 x 12#> mpg cyl disp hp drat wt qsec vs am gear carb n#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 32#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 32#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 32#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 32#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 32#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 32#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 32#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 32#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 32#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 32#> # … with 22 more rows
# add_count() is a short-hand for group_by() + add_tally()mtcars %>% add_count(cyl)
#> # A tibble: 32 x 12#> mpg cyl disp hp drat wt qsec vs am gear carb n#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 7#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 7#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 11#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 7#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 14#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 7#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 14#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 11#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 11#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 7#> # … with 22 more rows
# count() and tally() are designed so that you can call# them repeatedly, each time rolling up a level of detailspecies <- starwars %>% count(species, homeworld, sort = TRUE)species
#> # A tibble: 58 x 3#> species homeworld n#> <chr> <chr> <int>#> 1 Human Tatooine 8#> 2 Human Naboo 5#> 3 Human <NA> 5#> 4 Gungan Naboo 3#> 5 Human Alderaan 3#> 6 Droid Tatooine 2#> 7 Droid <NA> 2#> 8 Human Corellia 2#> 9 Human Coruscant 2#> 10 Kaminoan Kamino 2#> # … with 48 more rows
species %>% count(species, sort = TRUE)
#> # A tibble: 38 x 2#> species n#> <chr> <int>#> 1 Human 16#> 2 Droid 3#> 3 <NA> 3#> 4 Zabrak 2#> 5 Aleena 1#> 6 Besalisk 1#> 7 Cerean 1#> 8 Chagrian 1#> 9 Clawdite 1#> 10 Dug 1#> # … with 28 more rows
# Change the name of the newly created column:species <- starwars %>% count(species, homeworld, sort = TRUE, name = "n_species_by_homeworld")species
#> # A tibble: 58 x 3#> species homeworld n_species_by_homeworld#> <chr> <chr> <int>#> 1 Human Tatooine 8#> 2 Human Naboo 5#> 3 Human <NA> 5#> 4 Gungan Naboo 3#> 5 Human Alderaan 3#> 6 Droid Tatooine 2#> 7 Droid <NA> 2#> 8 Human Corellia 2#> 9 Human Coruscant 2#> 10 Kaminoan Kamino 2#> # … with 48 more rows
species %>% count(species, sort = TRUE, name = "n_species")
#> # A tibble: 38 x 2#> species n_species#> <chr> <int>#> 1 Human 16#> 2 Droid 3#> 3 <NA> 3#> 4 Zabrak 2#> 5 Aleena 1#> 6 Besalisk 1#> 7 Cerean 1#> 8 Chagrian 1#> 9 Clawdite 1#> 10 Dug 1#> # … with 28 more rows
# add_count() is useful for groupwise filtering# e.g.: show details for species that have a single memberstarwars %>% add_count(species) %>% filter(n == 1)
#> # A tibble: 29 x 14#> name height mass hair_color skin_color eye_color birth_year gender#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> #> 1 Gree… 173 74 <NA> green black 44 male #> 2 Jabb… 175 1358 <NA> green-tan… orange 600 herma…#> 3 Yoda 66 17 white green brown 896 male #> 4 Bossk 190 113 none green red 53 male #> 5 Ackb… 180 83 none brown mot… orange 41 male #> 6 Wick… 88 20 brown brown brown 8 male #> 7 Nien… 160 68 none grey black NA male #> 8 Nute… 191 90 none mottled g… red NA male #> 9 Watto 137 NA black blue, grey yellow NA male #> 10 Sebu… 112 40 none grey, red orange NA male #> # … with 19 more rows, and 6 more variables: homeworld <chr>, species <chr>,#> # films <list>, vehicles <list>, starships <list>, n <int>
