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r - 合并多个数据框，同时添加具有相应数据框名称的新列

问题描述

我有一个数据框列表

my_list <- list(structure(c("23000 Vs 23500", "23500 Vs 24000", "1.03546847852537", 
"0.735744771309744", "15", "29"), .Dim = 2:3, .Dimnames = list(
    NULL, c("Group", "EffectSize", "RequiredReplicates"))), structure(c("23500 Vs 24000", 
"24000 Vs 25000", "25000 Vs 25500", "0.735744771309744", "1.48620682621918", 
"0.418877850096638", "29", "7", "89"), .Dim = c(3L, 3L), .Dimnames = list(
    NULL, c("Group", "EffectSize", "RequiredReplicates"))), structure(c("26000 Vs 26500", 
"26500 Vs 27000", "27000 Vs 27500", "0.0739021800199834", "0.14116830704947", 
"0.135704984161555", "2874", "788", "852"), .Dim = c(3L, 3L), .Dimnames = list(
    NULL, c("Group", "EffectSize", "RequiredReplicates"))))
names(my_list) <- paste0("tt", 1:3)

我想要的是添加一个grp带有数据框名称的新列并将它们全部 rbind 以创建一个数据框。

  lapply(
      my_list,
      function(x) {
      x$grp <- deparse(substitute(x))
      rbind(x)
    }
  )

我想要的结果：

Group            EffectSize           RequiredReplicates       grp
  "23000 Vs 23500" "1.03546847852537"   "15"                   tt1
  "23500 Vs 24000" "0.735744771309744"  "29"                   tt1
  "23500 Vs 24000" "0.735744771309744"  "29"                   tt2
  "24000 Vs 25000" "1.48620682621918"   "7"                    tt2
  "25000 Vs 25500" "0.418877850096638"  "89"                   tt2
  "26000 Vs 26500" "0.0739021800199834" "2874"                 tt3
  "26500 Vs 27000" "0.14116830704947"   "788"                  tt3
  "27000 Vs 27500" "0.135704984161555"  "852                   tt3

谢谢你的帮助！

标签： r

解决方案

1) data.table将每个组件转换为 data.table 然后使用rbindlistwithidcol参数。

library(data.table)

my_list_nms <- setNames(my_list, paste0("tt", seq_along(my_list)))
rbindlist(lapply(my_list_nms, as.data.table), idcol = "id")

给出这个data.table：

    id          Group         EffectSize RequiredReplicates
1: tt1 23000 Vs 23500   1.03546847852537                 15
2: tt1 23500 Vs 24000  0.735744771309744                 29
3: tt2 23500 Vs 24000  0.735744771309744                 29
4: tt2 24000 Vs 25000   1.48620682621918                  7
5: tt2 25000 Vs 25500  0.418877850096638                 89
6: tt3 26000 Vs 26500 0.0739021800199834               2874
7: tt3 26500 Vs 27000   0.14116830704947                788
8: tt3 27000 Vs 27500  0.135704984161555                852

2) purrr 使用 purrr 和 tibble 也可以做到。 my_list_nms是从上面。

library(purrr)
library(tibble)

map_dfr(my_list_nms, as_data_frame, .id = "id")

给这个小标题：

# A tibble: 8 x 4
  id    Group          EffectSize         RequiredReplicates
  <chr> <chr>          <chr>              <chr>             
1 tt1   23000 Vs 23500 1.03546847852537   15                
2 tt1   23500 Vs 24000 0.735744771309744  29                
3 tt2   23500 Vs 24000 0.735744771309744  29                
4 tt2   24000 Vs 25000 1.48620682621918   7                 
5 tt2   25000 Vs 25500 0.418877850096638  89                
6 tt3   26000 Vs 26500 0.0739021800199834 2874              
7 tt3   26500 Vs 27000 0.14116830704947   788               
8 tt3   27000 Vs 27500 0.135704984161555  852

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