R dplyr group_nest 使用分组规范嵌套 tibble

group_nest(.tbl, ..., .key = "data", keep = FALSE)

其他分组函数：group_by()、group_map()、group_split()、group_trim()

#----- use case 1: a grouped data frame
iris %>%
  group_by(Species) %>%
  group_nest()
#> # A tibble: 3 × 2
#>   Species                  data
#>   <fct>      <list<tibble[,4]>>
#> 1 setosa               [50 × 4]
#> 2 versicolor           [50 × 4]
#> 3 virginica            [50 × 4]

# this can be useful if the grouped data has been altered before nesting
iris %>%
  group_by(Species) %>%
  filter(Sepal.Length > mean(Sepal.Length)) %>%
  group_nest()
#> # A tibble: 3 × 2
#>   Species                  data
#>   <fct>      <list<tibble[,4]>>
#> 1 setosa               [22 × 4]
#> 2 versicolor           [24 × 4]
#> 3 virginica            [22 × 4]

#----- use case 2: using group_nest() on a ungrouped data frame with
#                  a grouping specification that uses the data mask
starwars %>%
  group_nest(species, homeworld)
#> # A tibble: 58 × 3
#>    species  homeworld                  data
#>    <chr>    <chr>       <list<tibble[,12]>>
#>  1 Aleena   Aleen Minor            [1 × 12]
#>  2 Besalisk Ojom                   [1 × 12]
#>  3 Cerean   Cerea                  [1 × 12]
#>  4 Chagrian Champala               [1 × 12]
#>  5 Clawdite Zolan                  [1 × 12]
#>  6 Droid    Naboo                  [1 × 12]
#>  7 Droid    Tatooine               [2 × 12]
#>  8 Droid    NA                     [3 × 12]
#>  9 Dug      Malastare              [1 × 12]
#> 10 Ewok     Endor                  [1 × 12]
#> # ℹ 48 more rows