r-如何使用case_when在dplyr中应用不同的函数

Question

我的想法可能很天真。但是我想要基于第二个"0"来分割df的行[1:3]_&"；，使用tidyr::extract()

library(tidyr)
library(dplyr)
extract(col1, into = c("col1", "col2"), "^(.*?_.*?)_(.*)$")

并且df[4:6]的行基于第一"_">

extract(col1, into = c("col1", "col2"), "^(.*?)_(.*)$")

我正在考虑类似的东西

df %>% 
mutate(n=row_number())
mutate(col2=case_when
(n<=3 ~ extract(col1, into = c("col1", "col2"), "^(.*?_.*?)_(.*)$"), 
n>3 ~ extract(col1, into = c("col1", "col2"), "^(.*?)_(.*)$")
)

当然，这是大错特错的，但这在某种程度上可能吗？

示例数据：

df=tibble(col1 = c("2397_A_run379_CTTGTACT_S119_L004_R1_001", 
"3779_A_run535_TTATAGCC_S91_L003_R1_001", 
"4958_BV_run685_GCGTACGT_S89_L005_R1_001", 
"5126AA_S27_L004_R1_001",
"5126AF_S32_L004_R1_001",
"5126AL_S38_L004_R1_001"))
df
#> # A tibble: 6 × 1
#>   col1                                   
#>   <chr>                                  
#> 1 2397_A_run379_CTTGTACT_S119_L004_R1_001
#> 2 3779_A_run535_TTATAGCC_S91_L003_R1_001 
#> 3 4958_BV_run685_GCGTACGT_S89_L005_R1_001
#> 4 5126AA_S27_L004_R1_001                 
#> 5 5126AF_S32_L004_R1_001                 
#> 6 5126AL_S38_L004_R1_001

^{创建于2022-11-17，reprex v2.0.2}

Answer 1

如果模式是通过匹配_来提取子字符串，则前面的一个或多个字母后面跟着数字，

library(dplyr)
library(stringr)
df %>% 
mutate(col2 = str_extract(col1, "(?<=_)[A-Za-z]+\d+.*"))

-输出

# A tibble: 6 × 2
col1                                    col2                            
<chr>                                   <chr>                           
1 2397_A_run379_CTTGTACT_S119_L004_R1_001 run379_CTTGTACT_S119_L004_R1_001
2 3779_A_run535_TTATAGCC_S91_L003_R1_001  run535_TTATAGCC_S91_L003_R1_001 
3 4958_BV_run685_GCGTACGT_S89_L005_R1_001 run685_GCGTACGT_S89_L005_R1_001 
4 5126AA_S27_L004_R1_001                  S27_L004_R1_001                 
5 5126AF_S32_L004_R1_001                  S32_L004_R1_001                 
6 5126AL_S38_L004_R1_001                  S38_L004_R1_001 

---

或使用separate

library(tidyr)
separate(df, col1, into = c("col1", "col2"), 
sep = "(?<=[A-Z])_(?=[A-Za-z]+\d+)", extra = "merge")   

-输出

# A tibble: 6 × 2
col1    col2                            
<chr>   <chr>                           
1 2397_A  run379_CTTGTACT_S119_L004_R1_001
2 3779_A  run535_TTATAGCC_S91_L003_R1_001 
3 4958_BV run685_GCGTACGT_S89_L005_R1_001 
4 5126AA  S27_L004_R1_001                 
5 5126AF  S32_L004_R1_001                 
6 5126AL  S38_L004_R1_001      

Answer 2

tidyr::extract()获取并返回一个数据帧，在mutate()中使用会很困难。我会使用类似stringr::str_match():的东西

library(dplyr)
library(stringr)
df %>%
mutate(
row = row_number(),
col2 = case_when(
row < 4 ~ str_match(col1, ".+?_.+?_(.+)")[, 2],
row < 7 ~ str_match(col1, ".+?_(.+)")[, 2]
)
)

# A tibble: 6 × 3
col1                                      row col2                            
<chr>                                   <int> <chr>                           
1 2397_A_run379_CTTGTACT_S119_L004_R1_001     1 run379_CTTGTACT_S119_L004_R1_001
2 3779_A_run535_TTATAGCC_S91_L003_R1_001      2 run535_TTATAGCC_S91_L003_R1_001 
3 4958_BV_run685_GCGTACGT_S89_L005_R1_001     3 run685_GCGTACGT_S89_L005_R1_001 
4 5126AA_S27_L004_R1_001                      4 S27_L004_R1_001                 
5 5126AF_S32_L004_R1_001                      5 S32_L004_R1_001                 
6 5126AL_S38_L004_R1_001                      6 S38_L004_R1_001