将多个类别变量重塑为二进制响应变量 [英] Reshape multiple categorical variables to binary response variables

问题描述

我正在尝试转换以下格式:

I am trying to convert the following format:

mydata <- data.frame(movie = c("Titanic", "Departed"), 
                     actor1 = c("Leo", "Jack"), 
                     actor2 = c("Kate", "Leo"))

     movie actor1 actor2
1  Titanic    Leo   Kate
2 Departed   Jack    Leo

二进制响应变量:

     movie Leo Kate Jack
1  Titanic   1    1    0
2 Departed   1    0    1

我尝试了中所述的解决方案 将行数据转换为二进制列 但我可以让它适用于两个变量，而不是三个.

I tried the solution described in Convert row data to binary columns but I could get it to work for two variables, not three.

如果有一种干净的方法，我将不胜感激.

I would really appreciate if there is a clean way to do this.

推荐答案

基于tidyr的更新选项是转换为长形，使用complete填充缺少的电影和演员组合，然后将逻辑is.na测试转换为数值.然后重新变宽.

An updated tidyr-based option is to convert to long-shape, use complete to fill in missing combinations of movies and actors, and then just convert a logical is.na test to a numeric value. Then reshape back to wide.

library(tidyr)

mydata %>%
  pivot_longer(starts_with("actor"), names_to = "acted") %>%
  complete(movie, value) %>%
  dplyr::mutate(acted = as.numeric(!is.na(acted))) %>%
  pivot_wider(names_from = value, values_from = acted)
#> # A tibble: 2 x 4
#>   movie     Jack   Leo  Kate
#>   <fct>    <dbl> <dbl> <dbl>
#> 1 Departed     1     1     0
#> 2 Titanic      0     1     1

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