根据R

根据R

2024-05-18 • 问答

我有一个看起来像这样的数据框，其中有更多的行和列：

> df <- data.frame(country = c ("Australia","Australia","Angola","US","US"),year=c("1945","1946","1947"),leader = c("David","NA","Henry","Tom","Chris"),natural.death = c(0,NA,1,0),gdp.growth.rate=c(1,4,3,5,6,7,9))
> 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的条件的唯一领导者（列领导）的数量（natural.death == 1）。对于此df，我希望为Henry和Tom获得2个新列，其值分别为0,0和0,0 ，0,0分别。我最好根据natural.death中显示的数据顺序添加两个新列，分别称为id1和id2。我需要创建69个新专栏，因为那里有69个领导者阵亡，所以我正在寻找一种非手动方法来处理此问题。

我已经尝试过循环，例如，对于唯一的，列表化的，dcast的，虚拟的，但是不幸的是我什么都做不了。

我希望得到：

> df <- data.frame(country = c ("Australia",9),+                  id1=c(0,id2=c(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

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

library(tidyverse) df %>% mutate(id = ifelse(natural.death == 1,id = ifelse(is.na(id),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

chimper 回答：根据R

大家都在问