R 将宽数据转换为长数据

R Converting Wide Data to Long

如何转换我的数据:

example <- data.frame(RTD_1_LOC = c('A', 'B'), RTD_2_LOC = c('C', 'D'),
                      RTD_3_LOC = c('E', 'F'), RTD_4_LOC = c('G', 'H'),
                      RTD_5_LOC = c('I', 'J'),RTD_1_OFF = c('1', '2'), RTD_2_OFF = c('3', '4'),
                      RTD_3_OFF = c('5', '6'), RTD_4_OFF = c('7', '8'),
                      RTD_5_OFF = c('9', '10'))

对此:

example2 <- data.frame(RTD = c(1,1,2,2,3,3,4,4,5,5),LOC = c('A', 'B','C','D','E','F','G','H','I','J'),
                       OFF = c(1,2,3,4,5,6,7,8,9,10))

我一直在使用 tidyverse gather,但我最终得到了大约 50 列

ex <- gather(example,RTD, Location, RTD_1_LOC:RTD_5_LOC) 
ex$RTD <- sub('_LOC',"",ex$RTD)


ex3 <- gather(ex,RTD, Offset, RTD_1_OFF:RTD_5_OFF)
ex2$RTD <- sub('_OFF',"",ex2$RTD)

我们可以使用 tidyr 中的 pivot_longer 并指定 names_pattern 从列名中捕获组。由于 'RTD' 列应保留原样,因此在 names_to 中指定一个 'RTD' 向量和列值 (.value),以便 'RTD'将获取数字捕获 ((\d+) 和单词 ((\w+)) 'LOC', 'OFF' 将被创建为具有列值

的新列
library(dplyr)
library(tidyr)
 example %>% 
     pivot_longer(cols = everything(), 
      names_to = c("RTD", ".value"), names_pattern = "\w+_(\d+)_(\w+)")

-输出

# A tibble: 10 x 3
   RTD   LOC   OFF  
   <chr> <chr> <chr>
 1 1     A     1    
 2 2     C     3    
 3 3     E     5    
 4 4     G     7    
 5 5     I     9    
 6 1     B     2    
 7 2     D     4    
 8 3     F     6    
 9 4     H     8    
10 5     J     10