CODEWITHSUNDEEP
rdataframereplace
Seydou GORO
Seydou GORO

Reputation: 1285

replace value in multiple columns

Here is my dataframe:

ID <- 1:4
var1 <- c("yes","no","yes","no")
var2 <- c("no","no","yes","no")
var3 <- c("yes","yes","no","no")
data <- data.frame(ID, var1, var2, var3)

I want to replace all of the yes by 1 and no by 0 in order to have such a table below

  ID var1 var2 var3
1  1    1    0    1
2  2    0    0    1
3  3    1    1    0
4  4    0    0    0

Upvotes: 0

Views: 109

Answers (3)

akrun
akrun

Reputation: 887118

Using data.table

library(data.table)
setDT(data)[, (2:4) :=  lapply(.SD, function(x) as.integer(x == 'yes')), .SDcols = 2:4]

Upvotes: 0

Darren Tsai
Darren Tsai

Reputation: 35554

A base solution:

cbind(data[1], +(data[-1] == "yes"))

#   ID var1 var2 var3
# 1  1    1    0    1
# 2  2    0    0    1
# 3  3    1    1    0
# 4  4    0    0    0

Upvotes: 1

Duck
Duck

Reputation: 39595

One solution would be across() from tidyverse:

library(tidyverse)
#Data
ID<-1:4
var1<-c("yes","no","yes","no")
var2<-c("no","no","yes","no")
var3<-c("yes","yes","no","no")
#Code
data<-data.frame(ID,var1,var2,var3,stringsAsFactors = F)
#Solution
data %>%
  mutate(across(c(var1:var3), ~ ifelse(.=='yes', 1, 0)))

Output:

  ID var1 var2 var3
1  1    1    0    1
2  2    0    0    1
3  3    1    1    0
4  4    0    0    0

And a base R solution would be using indexing with the values yes/no:

#Solution 2
data[data=='yes']<-1
data[data=='no']<-0
data[,-1] <- sapply(data[,-1],as.numeric)

Output:

  ID var1 var2 var3
1  1    1    0    1
2  2    0    0    1
3  3    1    1    0
4  4    0    0    0

Upvotes: 1

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