我有dataframe_A，其中有一列，每行包含一个数据帧。
以下是我所说的数据帧的输入：
structure(list(spend = c("840.99", "1145.39", "1043.88", "1169.15",
"1249.75", "1197.57"), actions = list(structure(list(action_type = c("like",
"link_click", "post", "post_reaction", "page_engagement", "post_engagement"
), value = c("18", "205", "2", "28", "253", "235")), .Names =
c("action_type",
"value"), class = "data.frame", row.names = c(NA, 6L)), structure(list(
action_type = c("like", "link_click", "post", "post_reaction",
"page_engagement", "post_engagement"), value = c("26", "268",
"3", "33", "330", "304")), .Names = c("action_type", "value"
), class = "data.frame", row.names = c(NA, 6L)), structure(list(
action_type = c("like", "link_click", "post", "post_reaction",
"page_engagement", "post_engagement"), value = c("16", "214",
"2", "28", "260", "244")), .Names = c("action_type", "value"
), class = "data.frame", row.names = c(NA, 6L)), structure(list(
action_type = c("comment", "like", "link_click", "post",
"post_reaction", "page_engagement", "post_engagement"), value = c("2",
"14", "255", "2", "44", "317", "303")), .Names = c("action_type",
"value"), class = "data.frame", row.names = c(NA, 7L)), structure(list(
action_type = c("comment", "like", "link_click", "post",
"post_reaction", "page_engagement", "post_engagement"), value = c("1",
"15", "240", "1", "23", "280", "265")), .Names = c("action_type",
"value"), class = "data.frame", row.names = c(NA, 7L)), structure(list(
action_type = c("like", "link_click", "post", "post_reaction",
"page_engagement", "post_engagement"), value = c("16", "252",
"3", "32", "303", "287")), .Names = c("action_type", "value"
), class = "data.frame", row.names = c(NA, 6L))), date_start = c("2017-10-31",
"2017-11-01", "2017-11-02", "2017-11-03", "2017-11-04", "2017-11-05"
)), .Names = c("spend", "actions", "date_start"), class = c("data.table",
"data.frame"), row.names = c(NA, -6L), .internal.selfref = <pointer:
0x0000000000310788>)
输出如下：
spend actions date_start
1: 840.99 <data.frame> 2017-10-31
2: 1145.39 <data.frame> 2017-11-01
3: 1043.88 <data.frame> 2017-11-02
4: 1169.15 <data.frame> 2017-11-03
5: 1249.75 <data.frame> 2017-11-04
6: 1197.57 <data.frame> 2017-11-05
如果我只查看actions列，它看起来像这样：
df$actions
[[1]]
action_type value
1 like 18
2 link_click 205
3 post 2
4 post_reaction 28
5 page_engagement 253
6 post_engagement 235
[[2]]
action_type value
1 like 26
2 link_click 268
3 post 3
4 post_reaction 33
5 page_engagement 330
6 post_engagement 304
[[3]]
action_type value
1 like 16
2 link_click 214
3 post 2
4 post_reaction 28
5 page_engagement 260
6 post_engagement 244
[[4]]
action_type value
1 comment 2
2 like 14
3 link_click 255
4 post 2
5 post_reaction 44
6 page_engagement 317
7 post_engagement 303
[[5]]
action_type value
1 comment 1
2 like 15
3 link_click 240
4 post 1
5 post_reaction 23
6 page_engagement 280
7 post_engagement 265
[[6]]
action_type value
1 like 16
2 link_click 252
3 post 3
4 post_reaction 32
5 page_engagement 303
6 post_engagement 287
您可以看到每个数据框对应于原始数据框中的一行。如何提取这些数据框并使行名称将附加到原始数据框的新列。我希望我的最终结果是这样的（当我这样做时，格式化很奇怪所以我不能写最后3列，但那些也应该填充）：
spend actions date_start comment like link_click post post_reaction page_engagement post_engagement
1: 840.99 <data.frame> 2017-10-31 0 18 205 2
2: 1145.39 <data.frame> 2017-11-01 0 26 268 3
3: 1043.88 <data.frame> 2017-11-02 0 16 214 2
4: 1169.15 <data.frame> 2017-11-03 2 14 255 2
5: 1249.75 <data.frame> 2017-11-04 1 15 240 1
6: 1197.57 <data.frame> 2017-11-05 0 16 252 3
不确定这是否是正确的路线，但我正在考虑这些方面的内容并将结果重新绑定并将其绑定到原始数据帧：
t(df$actions[[1]])
任何帮助都会很棒，谢谢！
答案 0 :(得分：1)
library(tidyverse)
z1 %>%
as.tibble() %>%
unnest() %>%
spread(action_type, value) #convert to wide format
#output
spend date_start comment like link_click page_engagement post post_engagement post_reaction
* <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 1043.88 2017-11-02 NA 16 214 260 2 244 28
2 1145.39 2017-11-01 NA 26 268 330 3 304 33
3 1169.15 2017-11-03 2 14 255 317 2 303 44
4 1197.57 2017-11-05 NA 16 252 303 3 287 32
5 1249.75 2017-11-04 1 15 240 280 1 265 23
6 840.99 2017-10-31 NA 18 205 253 2 235 28
数据：
> dput(z1)
structure(list(spend = c("840.99", "1145.39", "1043.88", "1169.15",
"1249.75", "1197.57"), actions = list(structure(list(action_type = c("like",
"link_click", "post", "post_reaction", "page_engagement", "post_engagement"
), value = c("18", "205", "2", "28", "253", "235")), .Names = c("action_type",
"value"), class = "data.frame", row.names = c(NA, 6L)), structure(list(
action_type = c("like", "link_click", "post", "post_reaction",
"page_engagement", "post_engagement"), value = c("26", "268",
"3", "33", "330", "304")), .Names = c("action_type", "value"
), class = "data.frame", row.names = c(NA, 6L)), structure(list(
action_type = c("like", "link_click", "post", "post_reaction",
"page_engagement", "post_engagement"), value = c("16", "214",
"2", "28", "260", "244")), .Names = c("action_type", "value"
), class = "data.frame", row.names = c(NA, 6L)), structure(list(
action_type = c("comment", "like", "link_click", "post",
"post_reaction", "page_engagement", "post_engagement"), value = c("2",
"14", "255", "2", "44", "317", "303")), .Names = c("action_type",
"value"), class = "data.frame", row.names = c(NA, 7L)), structure(list(
action_type = c("comment", "like", "link_click", "post",
"post_reaction", "page_engagement", "post_engagement"), value = c("1",
"15", "240", "1", "23", "280", "265")), .Names = c("action_type",
"value"), class = "data.frame", row.names = c(NA, 7L)), structure(list(
action_type = c("like", "link_click", "post", "post_reaction",
"page_engagement", "post_engagement"), value = c("16", "252",
"3", "32", "303", "287")), .Names = c("action_type", "value"
), class = "data.frame", row.names = c(NA, 6L))), date_start = c("2017-10-31",
"2017-11-01", "2017-11-02", "2017-11-03", "2017-11-04", "2017-11-05"
)), .Names = c("spend", "actions", "date_start"), class = c("data.table",
"data.frame"), row.names = c(NA, -6L))