r - 根据多个条件创建新变量

Question

我正在尝试根据某些条件创建一个新变量。我有以下数据:

df <- data.frame(ID = c("A1","A1","A2","A2","A3","A4","A4"),
                 type = c("small","large","small","large","large","small","large"),
                 code = c("B9", "[0,20]","B9","[20,40]","[0,20]","B9","[40,60]" ))

给出:

    ID  type   code
1   A1  small   B9
2   A1  large   [0,20]
3   A2  small   B9
4   A2  large   [20,40]
5   A3  large   [0,20]
6   A4  small   B9
7   A4  large   [40,60]

我想创建一个新变量 (code2)，它基于 type == large 和 code 的相应值，同时按 ID< 分组/em>。所以 ID - A1 应该有 [0,20] 作为它的 code2。我想实现以下目标:

    ID  type   code       code2
1   A1  small   B9        [0,20]    
2   A1  large   [0,20]    [0,20] 
3   A2  small   B9        [20,40]
4   A2  large   [20,40]   [20,40]
5   A3  large   [0,20]    [0,20] 
6   A4  small   B9        [40,60]
7   A4  large   [40,60]   [40,60]

据我所知，我正在尝试使用 dplyr 和 ifelse，但没有成功。

Answer 1

我们可以在dplyr中使用分组操作，即按'ID'分组，提取'type'值为“large”的'code'(假设没有重复值'在每个“ID”中输入“

library(dplyr)
df <- df %>% 
   group_by(ID) %>%
   mutate(code2 = code[type == 'large']) %>%
   ungroup

-输出

df
# A tibble: 7 x 4
  ID    type  code    code2  
  <chr> <chr> <chr>   <chr>  
1 A1    small B9      [0,20] 
2 A1    large [0,20]  [0,20] 
3 A2    small B9      [20,40]
4 A2    large [20,40] [20,40]
5 A3    large [0,20]  [0,20] 
6 A4    small B9      [40,60]
7 A4    large [40,60] [40,60]

---

如果有重复，使用match，会给出第一个匹配索引的索引

df <- df %>%
       group_by(ID) %>%
       mutate(code2 = code[match('large', type)]) %>%
       ungroup