Question

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带有数据框名称的新列grp，然后将它们全部绑定成一个数据框。

  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

感谢您的帮助！

Answer 1

1）data.table 将每个组件转换为data.table，然后将rbindlist与idcol参数一起使用。

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")

提供此数据表。

    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 也可以使用purrr并进行点滴。 my_list_nms来自上方。

library(purrr)
library(tibble)

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

给出这个小标题：

# 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

合并多个数据框，同时还添加具有相应数据框名称的新列

1 个答案: