Reduce multiple values down to a single value

Create one or more scalar variables summarising the variables of an existing data.frame. Grouped data.frames will result in one row in the output for each group.

summarise(.data, ..., .groups = NULL)

summarize(.data, ..., .groups = NULL)

Arguments

.data	A data.frame.
...	Name-value pairs of summary functions. The name will be the name of the variable in the result.
.groups	character(1). Grouping structure of the result. "drop_last": drops the last level of grouping. "drop": all levels of grouping are dropped. "keep": keeps the same grouping structure as .data. When .groups is not specified, it is chosen based on the number of rows of the results: If all the results have 1 row, you get "drop_last". If the number of rows varies, you get "keep". In addition, a message informs you of that choice, unless the result is ungrouped, the option "poorman.summarise.inform" is set to FALSE. The value can be: A vector of length 1, e.g. min(x), n(), or sum(is.na(y)). A vector of length n, e.g. quantile().

Details

summarise() and summarize() are synonyms.

Examples

# A summary applied to ungrouped tbl returns a single row
mtcars %>%
  summarise(mean = mean(disp), n = n())
#>       mean  n
#> 1 230.7219 32

# Usually, you'll want to group first
mtcars %>%
  group_by(cyl) %>%
  summarise(mean = mean(disp), n = n())
#>   cyl     mean  n
#> 1   4 105.1364 11
#> 2   6 183.3143  7
#> 3   8 353.1000 14

# You can summarise to more than one value:
mtcars %>%
   group_by(cyl) %>%
   summarise(qs = quantile(disp, c(0.25, 0.75)), prob = c(0.25, 0.75))
#> `summarise()` has grouped output by 'cyl'. You can override using the `.groups` argument.
#>   cyl      x prob
#> 1   4  78.85 0.25
#> 2   4 120.65 0.75
#> 3   6 160.00 0.25
#> 4   6 196.30 0.75
#> 5   8 301.75 0.25
#> 6   8 390.00 0.75

# You use a data frame to create multiple columns so you can wrap
# this up into a function:
my_quantile <- function(x, probs) {
  data.frame(x = quantile(x, probs), probs = probs)
}
mtcars %>%
  group_by(cyl) %>%
  summarise(my_quantile(disp, c(0.25, 0.75)))
#> Error in my_quantile(disp, c(0.25, 0.75)): could not find function "my_quantile"

# Each summary call removes one grouping level (since that group
# is now just a single row)
mtcars %>%
  group_by(cyl, vs) %>%
  summarise(cyl_n = n()) %>%
  group_vars()
#> `summarise()` has grouped output by 'cyl'. You can override using the `.groups` argument.
#> [1] "cyl"