根据 R 中第二列的条件为列中的每个唯一值创建虚拟变量

Question

我有一个数据框，看起来有点像这样，有更多的行和列：

> df <- data.frame(country = c ("Australia","Australia","Australia","Angola","Angola","Angola","US","US","US"), year=c("1945","1946","1947"), leader = c("David", "NA", "NA", "NA","Henry","NA","Tom","NA","Chris"), natural.death = c(0,NA,NA,NA,1,NA,1,NA,0),gdp.growth.rate=c(1,4,3,5,6,1,5,7,9))
> df
    country year leader natural.death gdp.growth.rate
1 Australia 1945  David             0               1
2 Australia 1946     NA            NA               4
3 Australia 1947     NA            NA               3
4    Angola 1945     NA            NA               5
5    Angola 1946  Henry             1               6
6    Angola 1947     NA            NA               1
7        US 1945    Tom             1               5
8        US 1946     NA            NA               7
9        US 1947  Chris             0               9

我正在尝试添加 x 个新列，其中 x 对应于满足领导者死亡条件 (natural.death==1) 的唯一领导者（列领导者）的数量。在这个 df 的情况下，我希望为 Henry 和 Tom 获得 2 个新列，值为 0,0,0,0,1,0,0,0,0 和 0,0,0,0,0 ,0,1,0,0，分别。根据 natural.death 中显示的数据顺序，我最好使用名为 id1 和 id2 的两个新列。我需要创建 69 个新列，因为有 69 位领导人去世了，所以我正在寻找一种非手动方法来处理这个问题。

我已经尝试过循环，if、for、unique、mtabulate、dcast、dummies，但不幸的是我无法得到任何工作。

我希望得到：

> df <- data.frame(country = c ("Australia","Australia","Australia","Angola","Angola","Angola","US","US","US"), year=c("1945","1946","1947"), leader = c("David", "NA", "NA", "NA","Henry","NA","Tom","NA","Chris"), natural.death = c(0,NA,NA,NA,1,NA,1,NA,0),gdp.growth.rate=c(1,4,3,5,6,1,5,7,9),
+                  id1=c(0,0,0,0,1,0,0,0,0),id2=c(0,0,0,0,0,0,1,0,0))
> df
    country year leader natural.death gdp.growth.rate id1 id2
1 Australia 1945  David             0               1   0   0
2 Australia 1946     NA            NA               4   0   0
3 Australia 1947     NA            NA               3   0   0
4    Angola 1945     NA            NA               5   0   0
5    Angola 1946  Henry             1               6   1   0
6    Angola 1947     NA            NA               1   0   0
7        US 1945    Tom             1               5   0   1
8        US 1946     NA            NA               7   0   0
9        US 1947  Chris             0               9   0   0

Answer 1

这是一个粗略的方法

df <- data.frame(country = c ("Australia","Australia","Australia","Angola","Angola","Angola","US","US","US"), year=c("1945","1946","1947"), leader = c("David", "NA", "NA", "NA","Henry","NA","Tom","NA","Chris"), natural.death = c(0,NA,NA,NA,1,NA,1,NA,0),gdp.growth.rate=c(1,4,3,5,6,1,5,7,9))

tmp=which(df$natural.death==1) #index of deaths
lng=length(tmp) #number of deaths

#create matrix with zeros and lng columns, append to df
df=cbind(df,data.frame(matrix(0,nrow=nrow(df),ncol=lng)))
#change the newly added column names
colnames(df)[(ncol(df)-lng+1):ncol(df)]=paste0("id",1:lng)

for (i in 1:lng) { #loop over new columns
   df[tmp[i],paste0("id",i)]=1 #at index i of death and column id+i set df to 1
}

    country year leader natural.death gdp.growth.rate id1 id2
1 Australia 1945  David             0               1   0   0
2 Australia 1946     NA            NA               4   0   0
3 Australia 1947     NA            NA               3   0   0
4    Angola 1945     NA            NA               5   0   0
5    Angola 1946  Henry             1               6   1   0
6    Angola 1947     NA            NA               1   0   0
7        US 1945    Tom             1               5   0   1
8        US 1946     NA            NA               7   0   0
9        US 1947  Chris             0               9   0   0

Answer 2

以及 tidyverse 的方法。

library(tidyverse)

df %>% 
  mutate(id = ifelse(natural.death == 1, 1, 0),
         id = ifelse(is.na(id), 0, id),
         tmp = cumsum(id)) %>% 
  pivot_wider(names_prefix = "id",
              names_from = tmp,
              values_from = id,
              values_fill = list(id = 0)) %>% 
  select(-id0)

  country   year  leader natural.death gdp.growth.rate   id1   id2
  <fct>     <fct> <fct>          <dbl>           <dbl> <dbl> <dbl>
1 Australia 1945  David              0               1     0     0
2 Australia 1946  NA                NA               4     0     0
3 Australia 1947  NA                NA               3     0     0
4 Angola    1945  NA                NA               5     0     0
5 Angola    1946  Henry              1               6     1     0
6 Angola    1947  NA                NA               1     0     0
7 US        1945  Tom                1               5     0     1
8 US        1946  NA                NA               7     0     0
9 US        1947  Chris              0               9     0     0

根据 R 中第二列的条件为列中的每个唯一值创建虚拟变量

Create dummy variables for every unique value in a column based on a condition from a second column in R

r

dataframe

multiple-columns

dummy-variable