我正在通过Facebook API来获取商业见解，而返回的数据格式是嵌套列表。我已经将数据简化为一个列表列表。级别1的数据是一致的。级别2的数据始终包含在名为“操作”的列表中，但是在该子列表中的项目数变化的范围内是不规则的。如果没有针对该观察的操作，则actions子列表不存在。
我想将整个内容展平到一个数据框中，以使列的总补全表示第2级“操作”子列表中包含的所有可能项目。如果操作中不存在某些内容，则会插入NA。
我更喜欢使用purrr软件包。
示例数据：
my_list <- list(list(objective = "CONVERSIONS",
impressions = "4318", actions = list(list(action_device = "other",
action_type = "page_engagement", value = "2"), list(action_device = "other",
action_type = "post_engagement", value = "2"), list(action_device = "other",
action_type = "post_reaction", value = "1"), list(action_device = "other",
action_type = "video_view", value = "1"), list(action_device = "desktop",
action_type = "landing_page_view", value = "1"), list(
action_device = "desktop", action_type = "link_click",
value = "1"), list(action_device = "desktop", action_type = "page_engagement",
value = "18"), list(action_device = "desktop", action_type = "post_engagement",
value = "18"), list(action_device = "desktop", action_type = "video_view",
value = "17"), list(action_device = "iphone", action_type = "post",
value = "1"), list(action_device = "iphone", action_type = "landing_page_view",
value = "27"), list(action_device = "iphone", action_type = "link_click",
value = "30"), list(action_device = "iphone", action_type = "page_engagement",
value = "580"), list(action_device = "iphone", action_type = "post_engagement",
value = "580"), list(action_device = "iphone", action_type = "post_reaction",
value = "6"), list(action_device = "iphone", action_type = "video_view",
value = "543"), list(action_device = "ipad", action_type = "landing_page_view",
value = "2"), list(action_device = "ipad", action_type = "link_click",
value = "2"), list(action_device = "ipad", action_type = "page_engagement",
value = "29"), list(action_device = "ipad", action_type = "post_engagement",
value = "29"), list(action_device = "ipad", action_type = "video_view",
value = "27"), list(action_device = "android_smartphone",
action_type = "landing_page_view", value = "11"), list(
action_device = "android_smartphone", action_type = "link_click",
value = "12"), list(action_device = "android_smartphone",
action_type = "page_engagement", value = "222"), list(
action_device = "android_smartphone", action_type = "post_engagement",
value = "222"), list(action_device = "android_smartphone",
action_type = "post_reaction", value = "9"), list(action_device = "android_smartphone",
action_type = "video_view", value = "201"), list(action_device = "android_tablet",
action_type = "landing_page_view", value = "1"), list(
action_device = "android_tablet", action_type = "link_click",
value = "1"), list(action_device = "android_tablet",
action_type = "page_engagement", value = "7"), list(action_device = "android_tablet",
action_type = "post_engagement", value = "7"), list(action_device = "android_tablet",
action_type = "post_reaction", value = "1"), list(action_device = "android_tablet",
action_type = "video_view", value = "5")), date_start = "2018-09-23",
date_stop = "2018-09-23"), list(objective = "CONVERSIONS",
impressions = "8",
date_start = "2018-09-23", date_stop = "2018-09-23"), list(objective = "CONVERSIONS",
impressions = "75", actions = list(list(action_device = "desktop",
action_type = "page_engagement", value = "2"), list(action_device = "desktop",
action_type = "post_engagement", value = "2"), list(action_device = "desktop",
action_type = "video_view", value = "2"), list(action_device = "iphone",
action_type = "page_engagement", value = "12"), list(
action_device = "iphone", action_type = "post_engagement",
value = "12"), list(action_device = "iphone", action_type = "video_view",
value = "12"), list(action_device = "ipad", action_type = "page_engagement",
value = "5"), list(action_device = "ipad", action_type = "post_engagement",
value = "5"), list(action_device = "ipad", action_type = "video_view",
value = "5"), list(action_device = "android_smartphone",
action_type = "page_engagement", value = "3"), list(action_device = "android_smartphone",
action_type = "post_engagement", value = "3"), list(action_device = "android_smartphone",
action_type = "video_view", value = "3")), date_start = "2018-09-23",
date_stop = "2018-09-23"), list(objective = "CONVERSIONS",
impressions = "54",
actions = list(list(action_device = "iphone", action_type = "page_engagement",
value = "5"), list(action_device = "iphone", action_type = "post_engagement",
value = "5"), list(action_device = "iphone", action_type = "video_view",
value = "5"), list(action_device = "android_smartphone",
action_type = "page_engagement", value = "2"), list(action_device = "android_smartphone",
action_type = "post_engagement", value = "2"), list(action_device = "android_smartphone",
action_type = "video_view", value = "2")), date_start = "2018-09-23",
date_stop = "2018-09-23"))
答案 0 :(得分：1)
这项工作吗？
library(tidyverse)
nested_df <- map_dfr(my_list, ~modify_at(.,"actions",compose(list,bind_rows)))
# # A tibble: 4 x 5
# objective impressions actions date_start date_stop
# <chr> <chr> <list> <chr> <chr>
# 1 CONVERSIONS 4318 <tibble [33 x 3]> 2018-09-23 2018-09-23
# 2 CONVERSIONS 8 <NULL> 2018-09-23 2018-09-23
# 3 CONVERSIONS 75 <tibble [12 x 3]> 2018-09-23 2018-09-23
# 4 CONVERSIONS 54 <tibble [6 x 3]> 2018-09-23 2018-09-23
我们看到在某些没有actions的元素中，您可以轻松地删除这些行，
否则，如果您希望操作列为NA，则可以执行以下操作：
missing_actions <- lengths(nested_df$actions) == 0
nested_df$actions[missing_actions] <-
replicate(sum(missing_actions),
tibble(action_device = NA, action_type = NA, value = NA),F)
nested_df
# # A tibble: 4 x 5
# objective impressions actions date_start date_stop
# <chr> <chr> <list> <chr> <chr>
# 1 CONVERSIONS 4318 <tibble [33 x 3]> 2018-09-23 2018-09-23
# 2 CONVERSIONS 8 <tibble [1 x 3]> 2018-09-23 2018-09-23
# 3 CONVERSIONS 75 <tibble [12 x 3]> 2018-09-23 2018-09-23
# 4 CONVERSIONS 54 <tibble [6 x 3]> 2018-09-23 2018-09-23
unnest(nested_df)
# # A tibble: 52 x 7
# objective impressions date_start date_stop action_device action_type value
# <chr> <chr> <chr> <chr> <chr> <chr> <chr>
# 1 CONVERSIONS 4318 2018-09-23 2018-09-23 other page_engagement 2
# 2 CONVERSIONS 4318 2018-09-23 2018-09-23 other post_engagement 2
# 3 CONVERSIONS 4318 2018-09-23 2018-09-23 other post_reaction 1
# 4 CONVERSIONS 4318 2018-09-23 2018-09-23 other video_view 1
# 5 CONVERSIONS 4318 2018-09-23 2018-09-23 desktop landing_page_view 1
# 6 CONVERSIONS 4318 2018-09-23 2018-09-23 desktop link_click 1
# 7 CONVERSIONS 4318 2018-09-23 2018-09-23 desktop page_engagement 18
# 8 CONVERSIONS 4318 2018-09-23 2018-09-23 desktop post_engagement 18
# 9 CONVERSIONS 4318 2018-09-23 2018-09-23 desktop video_view 17
# 10 CONVERSIONS 4318 2018-09-23 2018-09-23 iphone post 1
# # ... with 42 more rows