转换数据框的列和行[重复]

Question

我有一个数据框：

ID   Value    Name    Score  Card_type  Card_number
1      NA     John     242      X           23
1     124     John      NA      X           23
1     124     John     242      Y           25
1     124     NA       242      Y           NA
2      55     Mike      NA      X           11
2      55     NA       431      X           11
2      55     Mike     431      Y           14
2      NA     Mike     431      Y           14

如您所见，IDs 有两个组 (Card_type)，用于列 Card_number。同样如您所见，具有相同ID 和Card_type 的某些行在某些列中具有相同的缺失值。我想要得到的是，让每个ID 成为一排填充列。并且Card_number 列必须拆分为Card_number_type_X 和Card_number_type_X 两列，Card_type 列必须删除。

所以想要的结果必须是这样的：

ID   Value    Name    Score   Card_number_type_X  Card_number_type_Y
1     124     John     242             23                   25
2      55     Mike     431             11                   14                 

我该怎么做？

Answer 1

一种方法是 fill 每个 ID 中的缺失值，然后获取仅保留唯一值的宽格式数据。

library(dplyr)
library(tidyr)

df %>%
  group_by(ID) %>%
  fill(everything(), .direction = 'updown') %>%
  pivot_wider(names_from = Card_type, values_from = Card_number, 
              values_fn = unique, names_prefix = 'Card_number_type_')

#     ID Value Name  Score Card_number_type_X Card_number_type_Y
#  <int> <int> <chr> <int>              <int>              <int>
#1     1   124 John    242                 23                 25
#2     2    55 Mike    431                 11                 14

---

看来原始数据和共享数据不一样，我们可以试试：

df %>%
    group_by(ID) %>%
    fill(everything(), .direction = 'updown') %>%
    distinct() %>%
    group_by(ID, Value, Name, Score) %>%
    mutate(row = row_number()) %>%
    pivot_wider(names_from = Card_type, values_from = Card_number, 
                names_prefix = 'Card_number_type_')

数据

df <- structure(list(ID = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), Value = c(NA, 
124L, 124L, 124L, 55L, 55L, 55L, NA), Name = c("John", "John", 
"John", NA, "Mike", NA, "Mike", "Mike"), Score = c(242L, NA, 
242L, 242L, NA, 431L, 431L, 431L), Card_type = c("X", "X", "Y", 
"Y", "X", "X", "Y", "Y"), Card_number = c(23L, 23L, 25L, NA, 
11L, 11L, 14L, 14L)), class = "data.frame", row.names = c(NA, 
-8L))