在 R 中，如何根据特定的行/列条件有选择地将一个单元格“复制并粘贴”到另一个单元格中？

Question

我有一些数据（见下文），其中我有参与者（ ID列）在三个变量（ Name_A 、 Name_B和Name_C ）上得分。 这些分数目前是根据X1Score 、 X2Score和X3Score列中的相关变量水平记录的。 我希望将这些分数“复制并粘贴”（因为缺少更好的短语）到相关列 - Name_A 、 Name_B和Name_C （当前填充为NA ） - 这样我就有了长格式的数据。 我该怎么做呢？

ID  X1      X1Score X2      X2Score X3      X3Score Name_A    Name_B  Name_C
1   Name_A  4.58    Name_C  4.79    Name_B  5.22    NA        NA      NA
2   Name_C  5.35    Name_B  5.33    Name_A  5.61    NA        NA      NA
3   Name_B  5.59    Name_C  5.48    Name_A  4.89    NA        NA      NA
4   Name_C  5.36    Name_B  5.04    Name_A  4.93    NA        NA      NA
5   Name_A  5.39    Name_B  5.27    Name_C  5.11    NA        NA      NA
6   Name_C  4.91    Name_A  4.99    Name_B  5.01    NA        NA      NA



df <- structure(list(ID = 1:6,
                         X1 = c("Name_A", "Name_C", "Name_B", "Name_C", "Name_A", "Name_C"),
                         X1Score = c(4.58, 5.35, 5.59, 5.36, 5.39, 4.91),
                         X2 = c("Name_C", "Name_B", "Name_C", "Name_B", "Name_B", "Name_A"),
                         X2Score = c(4.79, 5.33, 5.48, 5.04, 5.27, 4.99),
                         X3 = c("Name_B", "Name_A", "Name_A", "Name_A", "Name_C", "Name_B"),
                         X3Score = c(5.22, 5.61, 4.89, 4.93, 5.11, 5.01),
                         Name_A = c(NA, NA, NA, NA, NA, NA),
                         Name_B = c(NA, NA, NA, NA, NA, NA),
                         Name_C = c(NA, NA, NA, NA, NA, NA)),
                    row.names = c(NA, -6L), class = "data.frame")

#Edit：我上面的原始请求太简单了，虽然答案在技术上解决了这个问题，但我无法理解如何概括它。 因此，这是一个修改后的示例（其中唯一的主要区别是列的命名约定） - 尽管在上面的示例中使用相同的代码，但此示例会产生错误。 我希望通过我的问题的另一个例子，我将能够理解'X\\\\d+(.*)'行，因为它看起来是让它工作的关键。 这是更新的示例：

df <- structure(list(ID = 1:6,
                     X1_Name = c("Name_A", "Name_C", "Name_B", "Name_C", "Name_A", "Name_C"),
                     X1_Score = c(4.58, 5.35, 5.59, 5.36, 5.39, 4.91),
                     X5_Name = c("Name_C", "Name_B", "Name_C", "Name_B", "Name_B", "Name_A"),
                     X5_Score = c(4.79, 5.33, 5.48, 5.04, 5.27, 4.99),
                     X19_Name = c("Name_B", "Name_A", "Name_A", "Name_A", "Name_C", "Name_B"),
                     X19_Score = c(5.22, 5.61, 4.89, 4.93, 5.11, 5.01)),
                row.names = c(NA, -6L), class = "data.frame")

df %>%
  #get the data in long format creating two columns Name and Score
  pivot_longer(cols = -ID, 
               names_to = '.value',
               names_pattern = 'X\\d+(.*)') %>%
  #Get data in wide format. 
  pivot_wider(names_from = Name, values_from = Score)

Answer 1

您可以使用pivot_longer / pivot_wider执行整形 -

library(dplyr)
library(tidyr)

df %>%
  #To drop empty NA columns
  select(-starts_with('Name')) %>%
  #Rename X1 to X1Name, X2 to X2Name and so on
  rename_with(~paste0(., 'Name'), matches('^X\\d+$')) %>%
  #get the data in long format creating two columns Name and Score
  pivot_longer(cols = -ID, 
               names_to = '.value',
               names_pattern = 'X\\d+(.*)') %>%
  #Get data in wide format. 
  pivot_wider(names_from = Name, values_from = Score)

#     ID Name_A Name_C Name_B
#  <int>  <dbl>  <dbl>  <dbl>
#1     1   4.58   4.79   5.22
#2     2   5.61   5.35   5.33
#3     3   4.89   5.48   5.59
#4     4   4.93   5.36   5.04
#5     5   5.39   5.11   5.27
#6     6   4.99   4.91   5.01

如果您想保留数据中的所有其他列并分别添加这 3 列，您可以将数据集与原始数据集连接起来。

...Code from above %>%
   left_join(df %>% select(-starts_with('Name')), by = 'ID')