因子的条件重新编码

Question

我需要重新编码几个因子变量，但我总是失败。

假设我的数据是这样的：

df <- data.frame(a  = c("1","2","","Other"),
                 b  = c("3","","Other","Other"),
                 v1 = c("no","no","yes","yes"),
                 v2 = c("no","yes","no","no"),
                 v3 = c("no","yes","yes","no"))
df$a <- as.character(df$a)
df$b <- as.character(df$b)

df

>       a     b  v1  v2  v3
> 1     1     3  no  no  no
> 2     2        no yes yes
> 3       Other yes  no yes
> 4 Other Other yes  no  no

我要

v1 变为 "yes" if (a=="1" | b=="1"),

v2 为 "yes" if (a=="2" | b=="2") 和

v3 变为 "yes" if (a=="3" | b=="3").

所以模式是：

v# 变为 "yes" if (a="#" | b="#")。

我尝试使用 2 个循环使用 R base，但没有成功：

 for(i in c("a","b")){
   for(j in as.character(1:3)){
   df[which(df[,i]==j),][,c(paste("v",j,sep=""))] <- "yes"
   }}

我更愿意使用 dplyr::mutate 来执行此操作，但不知道如何...

Answer 1

在这种情况下，由于变量的数量比较少，简单的一组ifelse就可以解决问题：

df$v1<- ifelse(df$a==1 |df$b==1,"yes","no")
df$v2<- ifelse(df$a==2 |df$b==2,"yes","no")
df$v3<- ifelse(df$a==3 |df$b==3,"yes","no")

Answer 2

library(data.table)
dt = as.data.table(df) # or convert in-place using setDT

for (i in 1:3) dt[a == i | b == i, paste0('v', i) := 'yes']
#       a     b  v1  v2  v3
#1:     1     3 yes  no yes
#2:     2        no yes yes
#3:       Other yes  no yes
#4: Other Other yes  no  no

因子的条件重新编码

Conditional recoding of factor

r

dplyr

recode