如何在 R 中將分組變量分成兩個帶有字符串值的變量？

Question

我有一個看起來像這樣的數據：

Exp1 <- structure(list(Duration = c(159L, 170L, 140L, 95L, 216L, 142L
), Group = c("Personal Failure", "Personal Failure", "Nonpersonal Failure", 
             "Nonpersonal Success", "Personal Success", "Nonpersonal Failure"
)), row.names = c(NA, 6L), class = "data.frame")

我想將“組”列分成兩個不同的列，以便每個值（個人/非個人）的第一個單詞組成一個名為“類型”的列，第二個單詞（失敗/成功）組成另一個名為“成就”的列”。

我該怎么做？

這是我想要獲得的示例輸出：

Exp1 <- structure(list(Duration = c(159L, 170L, 140L, 95L, 216L, 142L
), type = c("Personal ", "Personal ", "Nonpersonal ", "Nonpersonal ", 
            "Personal ", "Nonpersonal "), achivement = c("Failure", "Failure", 
                                                         "Failure", "Success", "Success", "Failure")), row.names = c(NA, 
                                                                                                                     6L), class = "data.frame")

Answer 1

library(tidyr)
library(dplyr)

Exp1 %>% 
  separate(col = Group,into = c("Type","Achievement"),remove = FALSE)

  Duration               Group        Type Achievement
1      159    Personal Failure    Personal     Failure
2      170    Personal Failure    Personal     Failure
3      140 Nonpersonal Failure Nonpersonal     Failure
4       95 Nonpersonal Success Nonpersonal     Success
5      216    Personal Success    Personal     Success
6      142 Nonpersonal Failure Nonpersonal     Failure

Answer 2

基礎 R 解決方案：

split_vec_name <- "Group"
cbind(
   Exp1[,names(Exp1) != split_vec_name, drop = FALSE],
   strcapture(
      pattern = "(\\w+)\\s+(\\w+)",
      x = Exp1[,split_vec_name],
      proto = list(type = character(), achievement = character())
   )
)

Answer 3

你可以試試

library(dplyr)

Exp1 %>%
  rowwise %>%
  mutate(Type = (strsplit(Group, " ") %>% unlist)[1],
         Achievement = (strsplit(Group, " ") %>% unlist)[2]) 

  Duration Group               Type        Achievement
     <int> <chr>               <chr>       <chr>      
1      159 Personal Failure    Personal    Failure    
2      170 Personal Failure    Personal    Failure    
3      140 Nonpersonal Failure Nonpersonal Failure    
4       95 Nonpersonal Success Nonpersonal Success    
5      216 Personal Success    Personal    Success    
6      142 Nonpersonal Failure Nonpersonal Failure