按id从宽到长收集列[重复]

一种选择是 melt data.table 可能需要多次 patterns 在 measure 论点

library(data.table)
melt(setDT(drugs), measure = patterns('^drug_\\d+$', 'dos'),
     value.name = c('drug', 'dosage'))[, variable := NULL][order(id)]
#   id drug dosage
#1:  1    a     31
#2:  1    c     49
#3:  2    b     26
#4:  2    d     81
#5:  3    c     55
#6:  3    e     37
#7:  4    d      6
#8:  4    f     54
#9:  5    e     45
#10  5    g     17

在这里,“药物”在所有列中都很常见,所以我们需要创建一个独特的模式。一种方法是指定起始位置( ^ _ )一个或多个数字( \\d+ )最后( $

library(dplyr)
drugs %>% gather(key,val,-id) %>% mutate(key=gsub('_\\d','',key)) %>% #replace _1 and _2 at the end wiht nothing
          mutate(key=gsub('drug_','',key)) %>% group_by(key) %>%  #replace drug_ at the start of dos with nothin and gruop by key
          mutate(row=row_number()) %>% spread(key,val) %>%
          select(id,drug,dos,-row)


 # A tibble: 10 x 3
  id drug  dos  
  <int> <chr> <chr>
  1     1 a     31   
  2     1 c     49   
  3     2 b     26   
  4     2 d     81   
  5     3 c     55   
  6     3 e     37   
  7     4 d     6    
  8     4 f     54   
  9     5 e     45   
 10     5 g     17   
  Warning message:
  attributes are not identical across measure variables;
  they will be dropped
#This warning generated as we merged drug(chr) and dose(num) into one column (val)