make a new columns based on row-wise data in r-CodePudding

This is minimum reproducible example, but my real data is really huge so I cannot do it manually

id<-1:4
mathpass_1<-c("pass","fail","pass","fail")
mathpass_2<-c("fail","fail","fail","fail")
mathpass_3<-c("fail","fail","pass","pass")
mathpass_4<-c("fail","fail","pass","fail")

math<-data.frame(id,mathpass_1,mathpass_2,mathpass_3,mathpass_4)

so, the data is like this

> math
  id mathpass_1 mathpass_2 mathpass_3 mathpass_4
1  1       pass       fail       fail       fail
2  2       fail       fail       fail       fail
3  3       pass       fail       pass       pass
4  4       fail       fail       pass       fail

the Id is student's Id. I want to make an additional column ( binary variable) if a student get at least one pass, they will have "pass" and if a student did not get any pass, they will have "fail"

so, I want to make a column "pass" like this, but I made it manually.

id<-1:4
mathpass_1<-c("pass","fail","pass","fail")
mathpass_2<-c("fail","fail","fail","fail")
mathpass_3<-c("fail","fail","pass","pass")
mathpass_4<-c("fail","fail","pass","fail")
pass<-c("pass","fail","pass","pass")
math<-data.frame(id,mathpass_1,mathpass_2,mathpass_3,mathpass_4,pass)

> math
  id mathpass_1 mathpass_2 mathpass_3 mathpass_4 pass
1  1       pass       fail       fail       fail pass
2  2       fail       fail       fail       fail fail
3  3       pass       fail       pass       pass pass
4  4       fail       fail       pass       fail pass

However, my real data is really huge that I cannot do manually. How can I do this with code? (non-manual way)

CodePudding user response：

Try ifelse(rowSums(math[,-1]=="pass")>0,"pass","fail").

CodePudding user response：

You may try

library(dplyr)
math %>%
  mutate(pass = ifelse(rowSums(across(is.character, ~.x == "pass")) >0, "pass", "fail"))

  id mathpass_1 mathpass_2 mathpass_3 mathpass_4 pass
1  1       pass       fail       fail       fail pass
2  2       fail       fail       fail       fail fail
3  3       pass       fail       pass       pass pass
4  4       fail       fail       pass       fail pass