group_by: Group rows of a data frame

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Group rows of a data frame

Description

Converts a data frame into a grouped data frame. Pairs well with summarize() or mutate(). Operations that you do after group_by() will be performed by group. Grouping attributes are removed by dplyr::ungroup().

Details

First argument: a data frame.

Next argument: a variable to use as the basis for grouping. If you provide more than one variable, every distinct combination will be separate groups.

group_by(data, ...)

data %>% group_by(...)

See Also

Other dplyr verbs: filter(), select(), summarize(), mutate(), arrange()

Examples

# group_by() with summarize():

tibble(
  x = c(1, 1, 2, 2),
  y = c(1, 3, 0, 2)
) %>%
  group_by(x) %>%
  summarize(y_total = sum(y))

#> A tibble: 2 x 2
#>    x y_total
   <dbl>   <dbl>
#>    1       4
#>    2       2

-----------------------------------

# group_by multiple variables:

tibble(
  x = c(1, 1, 0, 0, 1),
  y = c(3, 2, 3, 2, 3),
  z = c(4, 6, 4, 6, 6)
) %>%
  group_by(x, y) %>%
  summarize(z_mean = mean(z))

#> # A tibble: 4 x 3
#> # Groups:   x [2]
#>    x     y z_mean
  <dbl> <dbl>  <dbl>
#>    0     2      6
#>    0     3      4
#>    1     2      6
#>    1     3      5

-----------------------------------

library(gapminder)

gapminder %>%
  group_by(continent) %>%
  summarize(gdp_mean = mean(gdpPercap))

#> # A tibble: 5 x 2
#> continent   gdp_mean
   <fct>          <dbl>
#> 1 Africa       2194.
#> 2 Americas     7136.
#> 3 Asia         7902.
#> 4 Europe      14469.
#> 5 Oceania     18622.

cobriant/qelp documentation built on July 1, 2022, 7:24 a.m.