r - 对应列为1时如何赋值？

Question

Year=c(2001,2001,2001,2001,2001,2001,
       2002,2002,2002,2002,2002,2002,
       2003,2003,2003,2003,2003,2003)
Factory=c("A","B","C","A","B","C",
          "A","B","C","A","B","C",
          "A","B","C","A","B","C")
Distribution=c(10023,12034,13948,10294,20494,34549,
               28979,34924,29845,18346,47377,65297,
               39081,85393,18273,82634,87635,64576,
               72368,25764,25863,45786,32789,38297)
Product=c("Cola","Cola","Cola","PepsiCo","PepsiCo","PepsiCo",
          "Cola","Cola","Cola","PepsiCo","PepsiCo","PepsiCo",
          "Cola","Cola","Cola","PepsiCo","PepsiCo","PepsiCo")

df=data.frame(Year,Factory,Distribution,Product)

这是我通过工厂分离的编码。

df %>%
  mutate(Product = 1) %>%
  pivot_wider(names_from = Factory,
              values_from = Product,
              values_fill = list(Product = 0))

Distribution列的值=1时如何分别给A B C赋值，按年份排列？

预期输出如下:

Answer 1

这是一个方法。使用 Product 作为 id 列，并在 reshape 后，将其从结果中删除。

library(dplyr)
library(tidyr)

df %>%
  pivot_wider(
    names_from = Factory,
    values_from = Distribution,
    values_fill = list(Distribution = 0)
  ) %>%
  select(-Product)
## A tibble: 6 x 4
#   Year     A     B     C
#  <dbl> <dbl> <dbl> <dbl>
#1  2001 10023 12034 13948
#2  2001 10294 20494 34549
#3  2002 28979 34924 29845
#4  2002 18346 47377 65297
#5  2003 39081 85393 18273
#6  2003 82634 87635 64576