例如,我有一个像这样的整洁数据框:
df <- tibble(id=1:2,
ctn=list(list(a="x",b=1),
list(a="y",b=2)))
# A tibble: 2 x 2
id ctn
<int> <list>
1 1 <list [2]>
2 2 <list [2]>
如何ctn
列向右取消嵌套,以便数据框如下所示:
# A tibble: 2 x 3
id a b
<int> <chr> <dbl>
1 1 x 1
2 2 y 2
带有dplyr
和purrr
df %>%
mutate(ctn = map(ctn, as_tibble)) %>%
unnest()
# A tibble: 2 x 3 id a b <int> <chr> <dbl> 1 1 x 1 2 2 y 2
一个选项是
library(data.table)
setDT(df)[, unlist(ctn, recursive = FALSE), id]
# id a b
#1: 1 x 1
#2: 2 y 2
或与tidyr
library(tidyverse)
df$ctn %>%
setNames(., df$id) %>%
bind_rows(., .id = 'id')
# A tibble: 2 x 3
# id a b
# <chr> <chr> <dbl>
#1 1 x 1
#2 2 y 2
我们现在可以使用rowwise()
以下命令(dplyr1.0.2
及以上(以整洁的方式执行此操作:
df %>% rowwise() %>% mutate(as_tibble(ctn))
# A tibble: 2 x 4
# Rowwise:
id ctn a b
<int> <list> <chr> <dbl>
1 1 <named list [2]> x 1
2 2 <named list [2]> y 2
坚持purrr
我们还可以:
df %>% mutate(map_dfr(ctn, as_tibble))
# A tibble: 2 x 4
id ctn a b
<int> <list> <chr> <dbl>
1 1 <named list [2]> x 1
2 2 <named list [2]> y 2