Как преобразовать списки, вложенные в таблицу, в одну таблицу с каждым элементом списка в новой строке?

Question

У меня есть тиббл с этой структурой (dput ниже):

# A tibble: 7 x 3
  Date  CC            Variance_Type
  <fct> <list>        <list>       
1 2-17  <dbl [8 x 2]> <chr [8]>    
2 2-18  <dbl [8 x 2]> <chr [8]>    
3 2-19  <dbl [8 x 2]> <chr [8]>    
4 2-20  <dbl [8 x 2]> <chr [8]>    
5 2-21  <dbl [8 x 2]> <chr [8]>    
6 2-22  <dbl [8 x 2]> <chr [8]>    
7 2-23  <dbl [8 x 2]> <chr [8]>    

Мой желаемый вывод - столбец 56 строк x 4, где:

1. Элементы каждый из списков был выведен в отдельную строку.
2. Значения в Date заполняют столбец, чтобы соответствовать элементам, которые в настоящее время находятся в их строке.
3. Столбцы вложенного таблицы в столбце CC разделены на отдельные столбцы.

Я пытался сделать это в тидиверсе с помощью комбинации mutate (), map () и bind_rows (), но я могу не заставит это работать. Любая помощь очень ценится.

Tibble:

structure(list(Date = structure(1:7, .Label = c("2-17", "2-18", 
"2-19", "2-20", "2-21", "2-22", "2-23"), class = "factor"), CC = list(
    structure(c(0.0292, 0.1803, 0.1063, 0.3555, 0.0227, 0.0471, 
    0.2588, 1, 2.92, 18.03, 10.63, 35.55, 2.27, 4.71, 25.88, 
    100), .Dim = c(8L, 2L), .Dimnames = list(c("Unique to Jsc             ", 
    "Unique to Uoc             ", "Unique to FF              ", 
    "Common to Jsc, and Uoc    ", "Common to Jsc, and FF     ", 
    "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
    "Total                     "), c("Coefficient", "    % Total"
    ))), structure(c(0.0414, 0.2307, 0.1813, 0.3428, 0.0408, 
    0.0137, 0.1494, 1, 4.14, 23.07, 18.13, 34.28, 4.08, 1.37, 
    14.94, 100), .Dim = c(8L, 2L), .Dimnames = list(c("Unique to Jsc             ", 
    "Unique to Uoc             ", "Unique to FF              ", 
    "Common to Jsc, and Uoc    ", "Common to Jsc, and FF     ", 
    "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
    "Total                     "), c("Coefficient", "    % Total"
    ))), structure(c(0.0348, 0.2298, 0.4534, 0.0453, 0.1252, 
    0.0406, 0.0709, 1, 3.48, 22.98, 45.34, 4.53, 12.52, 4.06, 
    7.09, 100), .Dim = c(8L, 2L), .Dimnames = list(c("Unique to Jsc             ", 
    "Unique to Uoc             ", "Unique to FF              ", 
    "Common to Jsc, and Uoc    ", "Common to Jsc, and FF     ", 
    "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
    "Total                     "), c("Coefficient", "    % Total"
    ))), structure(c(0.0693, 0.1241, 0.3104, 0.0885, 0.1706, 
    0.0563, 0.1807, 1, 6.93, 12.41, 31.04, 8.85, 17.06, 5.63, 
    18.07, 100), .Dim = c(8L, 2L), .Dimnames = list(c("Unique to Jsc             ", 
    "Unique to Uoc             ", "Unique to FF              ", 
    "Common to Jsc, and Uoc    ", "Common to Jsc, and FF     ", 
    "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
    "Total                     "), c("Coefficient", "    % Total"
    ))), structure(c(0.0431, 0.1621, 0.3896, 0.2243, 0.1005, 
    -0.0339, 0.1143, 1, 4.31, 16.21, 38.96, 22.43, 10.05, -3.39, 
    11.43, 100), .Dim = c(8L, 2L), .Dimnames = list(c("Unique to Jsc             ", 
    "Unique to Uoc             ", "Unique to FF              ", 
    "Common to Jsc, and Uoc    ", "Common to Jsc, and FF     ", 
    "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
    "Total                     "), c("Coefficient", "    % Total"
    ))), structure(c(0.0656, 0.1021, 0.2638, 0.1299, 0.2102, 
    0.0061, 0.2223, 1, 6.56, 10.21, 26.38, 12.99, 21.02, 0.61, 
    22.23, 100), .Dim = c(8L, 2L), .Dimnames = list(c("Unique to Jsc             ", 
    "Unique to Uoc             ", "Unique to FF              ", 
    "Common to Jsc, and Uoc    ", "Common to Jsc, and FF     ", 
    "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
    "Total                     "), c("Coefficient", "    % Total"
    ))), structure(c(0.0802, 0.1114, 0.6962, 0.0845, 0.1544, 
    -0.0958, -0.0309, 1, 8.02, 11.14, 69.62, 8.45, 15.44, -9.58, 
    -3.09, 100), .Dim = c(8L, 2L), .Dimnames = list(c("Unique to Jsc             ", 
    "Unique to Uoc             ", "Unique to FF              ", 
    "Common to Jsc, and Uoc    ", "Common to Jsc, and FF     ", 
    "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
    "Total                     "), c("Coefficient", "    % Total"
    )))), Variance_Type = list(c("Unique to Jsc             ", 
"Unique to Uoc             ", "Unique to FF              ", "Common to Jsc, and Uoc    ", 
"Common to Jsc, and FF     ", "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
"Total                     "), c("Unique to Jsc             ", 
"Unique to Uoc             ", "Unique to FF              ", "Common to Jsc, and Uoc    ", 
"Common to Jsc, and FF     ", "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
"Total                     "), c("Unique to Jsc             ", 
"Unique to Uoc             ", "Unique to FF              ", "Common to Jsc, and Uoc    ", 
"Common to Jsc, and FF     ", "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
"Total                     "), c("Unique to Jsc             ", 
"Unique to Uoc             ", "Unique to FF              ", "Common to Jsc, and Uoc    ", 
"Common to Jsc, and FF     ", "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
"Total                     "), c("Unique to Jsc             ", 
"Unique to Uoc             ", "Unique to FF              ", "Common to Jsc, and Uoc    ", 
"Common to Jsc, and FF     ", "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
"Total                     "), c("Unique to Jsc             ", 
"Unique to Uoc             ", "Unique to FF              ", "Common to Jsc, and Uoc    ", 
"Common to Jsc, and FF     ", "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
"Total                     "), c("Unique to Jsc             ", 
"Unique to Uoc             ", "Unique to FF              ", "Common to Jsc, and Uoc    ", 
"Common to Jsc, and FF     ", "Common to Uoc, and FF     ", "Common to Jsc, Uoc, and FF", 
"Total                     "))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -7L))

Answer 1

Вот еще одно решение на основе пакета data.table:

library(data.table)
df2 <- setDT(df)[, as.data.table(.SD$CC[[1]], .SD[["Variance_Type"]]), Date]
setnames(df2, "rn", "Variance_Type")

df2
#       Date              Variance_Type Coefficient     % Total
#  1:   2-17 Unique to Jsc                   0.0292        2.92
#  2:   2-17 Unique to Uoc                   0.1803       18.03
#  3:   2-17 Unique to FF                    0.1063       10.63
#  4:   2-17 Common to Jsc, and Uoc          0.3555       35.55
#  5:   2-17 Common to Jsc, and FF           0.0227        2.27
#  6:   2-17 Common to Uoc, and FF           0.0471        4.71
#  7:   2-17 Common to Jsc, Uoc, and FF      0.2588       25.88
#  8:   2-17 Total                           1.0000      100.00
#  9:   2-18 Unique to Jsc                   0.0414        4.14
# 10:   2-18 Unique to Uoc                   0.2307       23.07
# 11:   2-18 Unique to FF                    0.1813       18.13
# 12:   2-18 Common to Jsc, and Uoc          0.3428       34.28
# 13:   2-18 Common to Jsc, and FF           0.0408        4.08
# 14:   2-18 Common to Uoc, and FF           0.0137        1.37
# 15:   2-18 Common to Jsc, Uoc, and FF      0.1494       14.94
# 16:   2-18 Total                           1.0000      100.00
# 17:   2-19 Unique to Jsc                   0.0348        3.48
# 18:   2-19 Unique to Uoc                   0.2298       22.98
# 19:   2-19 Unique to FF                    0.4534       45.34
# 20:   2-19 Common to Jsc, and Uoc          0.0453        4.53
# 21:   2-19 Common to Jsc, and FF           0.1252       12.52
# 22:   2-19 Common to Uoc, and FF           0.0406        4.06
# 23:   2-19 Common to Jsc, Uoc, and FF      0.0709        7.09
# ....

Answer 2

Хотя обычно это тип проблемы, с которой unnest() из tidyr поможет, ваша переменная CC представляет собой матрицу вместо data.frame (или tibble). Это вызывает некоторые проблемы. Как только вы преобразуете матрицу в data.frame, я думаю, вы найдете unnest() инструментом go.

Моим первым шагом было l oop через матрицы в CC и преобразовать их в data.frames, используя purrr :: map l oop в пределах mutate(). Затем я использую unnest() для одновременного удаления обеих переменных.

Вот как это работает после tidyr версия 1.0.0.

library(tidyr)
library(purrr)
library(dplyr)
dat %>%
     mutate(CC = map(CC, as.data.frame) ) %>%
     unnest(cols = c(CC, Variance_Type) )

# A tibble: 56 x 4
   Date  Coefficient `    % Total` Variance_Type               
   <fct>       <dbl>         <dbl> <chr>                       
 1 2-17       0.0292          2.92 "Unique to Jsc             "
 2 2-17       0.180          18.0  "Unique to Uoc             "
 3 2-17       0.106          10.6  "Unique to FF              "
 4 2-17       0.356          35.6  "Common to Jsc, and Uoc    "
 5 2-17       0.0227          2.27 "Common to Jsc, and FF     "
 6 2-17       0.0471          4.71 "Common to Uoc, and FF     "
 7 2-17       0.259          25.9  Common to Jsc, Uoc, and FF  
 8 2-17       1             100    "Total                     "
 9 2-18       0.0414          4.14 "Unique to Jsc             "
10 2-18       0.231          23.1  "Unique to Uoc             "

Для предыдущих версий tidyr , код unnest() выглядит немного иначе.

dat %>%
     mutate(CC = map(CC, as.data.frame) ) %>%
     unnest(CC, Variance_Type )