How to use forloop to create a sequence of columns - r

Question

I need to create the variable x out of the variable y as below.
df$x<-0
df$x<-ifelse(df$y==0 | df$y==1, 1, 0)
df$x[is.na(df$x)] <- 0
However i hhave y ranging from 1 to 52, which means i need to create x1 thru x52. I am an avid stata user and it is pretty straight forward to do using the forval function. However I am having difficulties doing it in R. I thought about the following, but it didn't workout very well:
for (i in 1:52){
df$x[i] <- 0
.
.
.
}
I thought i could let r replace the i by the values from the loop the same way stata does.
thanks

Answer 1

Try something like this. Here an example using dummy data:
set.seed(123)
#Data
df <- as.data.frame(matrix(rnorm(520),nrow = 10,ncol = 52))
names(df) <- paste0('y',1:52)
#new names
vals <- paste0('x',1:52)
#Loop
for(i in vals)
{
df[[i]]<-0
df[[i]]<-ifelse(df[[gsub('x','y',i)]]==0 | df[[gsub('x','y',i)]]==1, 1, 0)
df[[i]][is.na(df[[i]])] <- 0
}

Answer 2

Suppose you had data that looked something like this:
data
x1 x2 x3 x4 x5 x6 x7 x8 x9 x10
1 1 3 0 NA 3 NA 3 1 2 3
2 1 1 NA NA 3 0 3 3 0 0
3 0 1 1 0 2 2 1 1 0 1
4 0 NA 2 1 3 2 NA 0 2 0
5 1 2 NA 2 0 1 2 3 2 3
6 3 NA 1 3 NA NA NA 3 NA 3
7 2 NA 3 3 NA 0 NA 1 1 1
8 NA 3 2 1 1 NA 1 0 1 2
9 0 1 0 NA NA 0 2 0 NA 2
10 1 0 3 0 3 2 NA 0 1 2
One approach might be to use dplyr::mutate with across:
library(tidyverse)
data %>%
mutate(across(everything(),~ ifelse(. %in% c(0,1), 1, 0),
.names = "y{.col}")) %>%
rename_all(~str_replace(.,"yx","y"))
x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 y1 y2 y3 y4 y5 y6 y7 y8 y9 y10
1 2 1 2 2 2 2 0 1 1 0 0 1 0 0 0 0 1 1 1 1
2 3 2 3 1 3 3 3 2 0 1 0 0 0 1 0 0 0 0 1 1
3 0 2 2 1 0 2 3 0 2 0 1 0 0 1 1 0 0 1 0 1
4 2 2 3 1 0 0 1 1 2 3 0 0 0 1 1 1 1 1 0 0
5 1 3 1 2 2 2 3 2 3 3 1 0 1 0 0 0 0 0 0 0
6 3 1 1 1 0 3 2 2 1 2 0 1 1 1 1 0 0 0 1 0
7 1 1 3 1 3 1 1 0 1 2 1 1 0 1 0 1 1 1 1 0
8 1 2 3 3 2 1 2 2 2 0 1 0 0 0 0 1 0 0 0 1
9 1 2 3 0 2 3 0 0 2 1 1 0 0 1 0 0 1 1 0 1
10 2 0 1 0 3 2 3 2 2 3 0 1 1 1 0 0 0 0 0 0
Example data:
set.seed(123)
data <- as.data.frame(matrix(sample(c(NA,0:3),100,replace = TRUE),ncol =10))
names(data) <- paste0("x",1:10)