R dplyr summarise 將每組匯總為一行

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

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

其他單表動詞： arrange() 、 filter() 、 mutate() 、 reframe() 、 rename() 、 select() 、 slice()

# 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())
#> # A tibble: 3 × 3
#>     cyl  mean     n
#>   <dbl> <dbl> <int>
#> 1     4  105.    11
#> 2     6  183.     7
#> 3     8  353.    14

# 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"

# BEWARE: reusing variables may lead to unexpected results
mtcars %>%
  group_by(cyl) %>%
  summarise(disp = mean(disp), sd = sd(disp))
#> # A tibble: 3 × 3
#>     cyl  disp    sd
#>   <dbl> <dbl> <dbl>
#> 1     4  105.    NA
#> 2     6  183.    NA
#> 3     8  353.    NA

# Refer to column names stored as strings with the `.data` pronoun:
var <- "mass"
summarise(starwars, avg = mean(.data[[var]], na.rm = TRUE))
#> # A tibble: 1 × 1
#>     avg
#>   <dbl>
#> 1  97.3
# Learn more in ?rlang::args_data_masking

# In dplyr 1.1.0, returning multiple rows per group was deprecated in favor
# of `reframe()`, which never messages and always returns an ungrouped
# result:
mtcars %>%
   group_by(cyl) %>%
   summarise(qs = quantile(disp, c(0.25, 0.75)), prob = c(0.25, 0.75))
#> Warning: Returning more (or less) than 1 row per `summarise()` group was
#> deprecated in dplyr 1.1.0.
#> ℹ Please use `reframe()` instead.
#> ℹ When switching from `summarise()` to `reframe()`, remember that
#>   `reframe()` always returns an ungrouped data frame and adjust
#>   accordingly.
#> `summarise()` has grouped output by 'cyl'. You can override using the
#> `.groups` argument.
#> # A tibble: 6 × 3
#> # Groups:   cyl [3]
#>     cyl    qs  prob
#>   <dbl> <dbl> <dbl>
#> 1     4  78.8  0.25
#> 2     4 121.   0.75
#> 3     6 160    0.25
#> 4     6 196.   0.75
#> 5     8 302.   0.25
#> 6     8 390    0.75
# ->
mtcars %>%
   group_by(cyl) %>%
   reframe(qs = quantile(disp, c(0.25, 0.75)), prob = c(0.25, 0.75))
#> # A tibble: 6 × 3
#>     cyl    qs  prob
#>   <dbl> <dbl> <dbl>
#> 1     4  78.8  0.25
#> 2     4 121.   0.75
#> 3     6 160    0.25
#> 4     6 196.   0.75
#> 5     8 302.   0.25
#> 6     8 390    0.75