使用 pivot_longer 創建多個值列

Question

您可以在pivot_longer()中指定多個值列嗎？

我的原始數據（發布在下面）我必須轉置為更廣泛的格式。 然后我想獲取這個新的轉置數據並將其恢復為原始格式（假設我做了一些轉換/並且不能使用原始數據）。 要重新轉置回更長的格式，我必須同時使用pivot_longer()然后pivot_wider()因為有多個值我想成為它們自己的列。

如果可能的話，我想避免使用pivot_wider()並在重新轉置數據時使用pivot_longer() 。

作為旁注，每行的唯一標識符是 id 和報告的組合。

代碼

dfa <- dfx %>% 
  pivot_wider(
    id_cols = id,
    names_from = report,
    values_from = c(pts,
                    p1, p2, p3,p4,p5,
                    d1,d2,d3,d4,d5)
  )


df_return <- dfa %>% 
  pivot_longer(cols = !id,
               names_to = c('vars','report'),
               names_pattern = "([a-z0-9]+)_(.*)",
               values_drop_na = TRUE) %>% 
  pivot_wider(id_cols = c(id, report),
              names_from = vars,
              values_from = value)

數據

structure(list(pts = c(431L, 167L, 167L, 760L, 348L, 768L, 619L, 
169L, 416L, 155L, 47L, 37L, 6L, 17L, 22L, 1L, 149L, 3L, 284L, 
7L), d1 = c(129L, 48L, 52L, 166L, 90L, 178L, 184L, 20L, 158L, 
42L, 3L, 15L, 2L, 7L, 9L, 0L, 54L, 1L, 69L, 6L), d2 = c(172L, 
67L, 64L, 257L, 132L, 255L, 261L, 30L, 201L, 61L, 9L, 20L, 2L, 
9L, 12L, 0L, 69L, 1L, 123L, 6L), d3 = c(205L, 77L, 73L, 312L, 
153L, 307L, 310L, 39L, 235L, 70L, 12L, 21L, 2L, 10L, 12L, 0L, 
77L, 2L, 139L, 6L), d4 = c(227L, 81L, 82L, 363L, 177L, 350L, 
342L, 52L, 257L, 75L, 15L, 24L, 2L, 12L, 13L, 0L, 86L, 2L, 151L, 
6L), d5 = c(248L, 88L, 92L, 414L, 192L, 387L, 374L, 66L, 279L, 
86L, 16L, 26L, 2L, 12L, 15L, 0L, 90L, 3L, 164L, 7L), report = c("2006", 
"2006", "2006", "2006", "2006", "2006", "2006", "2006", "2006", 
"2006", "2006", "2006", "2006", "2006", "2006", "2006", "2006", 
"2006", "2006", "2006"), p1 = c(1.0360364394094, 1.22979866735429, 
1.21423740998677, 0.87891144382145, 0.810310827130179, 0.965901663505148, 
1.02621739486337, 0.69319116444678, 1.18938130906092, 1.04220816515009, 
0.683545688193799, 1.05179228560845, 1.51468104603873, 1.15200888955888, 
0.948041330809858, 0, 1.23227405154205, 3.11155226007598, 0.908056299174703, 
1.57712371536702), p2 = c(0.986884800185635, 1.23066225499351, 
1.07336930339221, 0.966734485786667, 0.87421381769247, 0.974775549615439, 
1.06274655160121, 0.705150638862953, 1.12934487417415, 1.10234720984265, 
1.11084642794988, 1.06558505521222, 1.0197697665798, 1.15605466288868, 
1.01469386643771, 0, 1.17689541437029, 1.42783711234222, 1.16124019281912, 
1.27756288696848), p3 = c(0.993575954694177, 1.17968893104311, 
1.02608313159672, 0.965200422661265, 0.862910478266102, 0.976436243011877, 
1.06679768502287, 0.722966824498357, 1.12591016481614, 1.05867627021151, 
1.11227024088529, 0.98275117259764, 0.803738347803303, 1.09341228936369, 
0.878291424560146, 0, 1.10500006213832, 1.93128861370172, 1.0949534752299, 
1.14755029569502), p4 = c(0.986244633210798, 1.08520792731261, 
1.01128789684232, 0.977245321880205, 0.89785754450165, 0.981536130349165, 
1.04454959427709, 0.807825580390444, 1.1035817255901, 1.00192975678877, 
1.14371311954082, 1.02812279984398, 0.66742040677939, 1.15526702119886, 
0.878479047328667, 0, 1.10559111180852, 1.4717526513624, 1.05479137550321, 
1.07005088091939), p5 = c(0.992583778223324, 1.06016737802091, 
1.02253158347207, 1.00026491073882, 0.896290873874826, 0.985549150023704, 
1.04187931404895, 0.886647217836043, 1.09837506943384, 1.0323002052873, 
1.05833769015682, 1.05042831618603, 0.592515872759586, 1.05106420250504, 
0.961672664191663, 0, 1.05868657273466, 1.81304485775152, 1.04168095802127, 
1.19437925124365), id = c("ID 1", "ID 2", "ID 3", "ID 4", "ID 5", 
"ID 6", "ID 7", "ID 8", "ID 9", "ID 10", "ID 11", "ID 12", "ID 13", 
"ID 14", "ID 15", "ID 16", "ID 17", "ID 18", "ID 19", "ID 20"
)), row.names = c(NA, 20L), class = "data.frame")

Answer 1

我們可能需要names_to中的.value ，它選擇_之前列名的前綴部分作為列值，'report' 將返回后綴列名

library(tidyr)
pivot_longer(dfa, cols = -id, names_to = c(".value", "report"), 
      names_sep = "_")

-輸出

# A tibble: 20 × 13
   id    report   pts    p1    p2    p3    p4    p5    d1    d2    d3    d4    d5
   <chr> <chr>  <int> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <int> <int> <int> <int>
 1 ID 1  2006     431 1.04  0.987 0.994 0.986 0.993   129   172   205   227   248
 2 ID 2  2006     167 1.23  1.23  1.18  1.09  1.06     48    67    77    81    88
 3 ID 3  2006     167 1.21  1.07  1.03  1.01  1.02     52    64    73    82    92
 4 ID 4  2006     760 0.879 0.967 0.965 0.977 1.00    166   257   312   363   414
 5 ID 5  2006     348 0.810 0.874 0.863 0.898 0.896    90   132   153   177   192
 6 ID 6  2006     768 0.966 0.975 0.976 0.982 0.986   178   255   307   350   387
 7 ID 7  2006     619 1.03  1.06  1.07  1.04  1.04    184   261   310   342   374
 8 ID 8  2006     169 0.693 0.705 0.723 0.808 0.887    20    30    39    52    66
 9 ID 9  2006     416 1.19  1.13  1.13  1.10  1.10    158   201   235   257   279
10 ID 10 2006     155 1.04  1.10  1.06  1.00  1.03     42    61    70    75    86
11 ID 11 2006      47 0.684 1.11  1.11  1.14  1.06      3     9    12    15    16
12 ID 12 2006      37 1.05  1.07  0.983 1.03  1.05     15    20    21    24    26
13 ID 13 2006       6 1.51  1.02  0.804 0.667 0.593     2     2     2     2     2
14 ID 14 2006      17 1.15  1.16  1.09  1.16  1.05      7     9    10    12    12
15 ID 15 2006      22 0.948 1.01  0.878 0.878 0.962     9    12    12    13    15
16 ID 16 2006       1 0     0     0     0     0         0     0     0     0     0
17 ID 17 2006     149 1.23  1.18  1.11  1.11  1.06     54    69    77    86    90
18 ID 18 2006       3 3.11  1.43  1.93  1.47  1.81      1     1     2     2     3
19 ID 19 2006     284 0.908 1.16  1.09  1.05  1.04     69   123   139   151   164
20 ID 20 2006       7 1.58  1.28  1.15  1.07  1.19      6     6     6     6     7