How can I recode 0 to 1 and 1 to 0 for columns i1:i3 in the below sample dataset?
df <- data.frame(id = c(11,22,33),
i1 = c(0,1,NA),
i2 = c(1,1,0),
i3 = c(0,NA,1))
> df
id i1 i2 i3
1 11 0 1 0
2 22 1 1 NA
3 33 NA 0 1
I have tens of columns starting with i... So I need a indexing condition to apply only for those columns. The desired output would be:
> df1
id i1 i2 i3
1 11 1 0 1
2 22 0 0 NA
3 33 NA 1 0
You could approach this by indexing; would work fine if all variables beyond the id column begin with i as in the question.
df[, 2:4] <- ifelse(df[, 2:4] == 0, 1, 0)
# or more succinctly, following the examples of others, and still using `ifelse`
df[-1] <- ifelse(df[-1] == 0, 1, 0)
df
#> id i1 i2 i3
#> 1 11 1 0 1
#> 2 22 0 0 NA
#> 3 33 NA 1 0
Created on 2022-10-10 with reprex v2.0.2
We can just negate and coerce
df[-1] <- +(!df[-1])
-output
> df
id i1 i2 i3
1 11 1 0 1
2 22 0 0 NA
3 33 NA 1 0
We can simply use -
> df[-1] <- 1 - df[-1]
> df
id i1 i2 i3
1 11 1 0 1
2 22 0 0 NA
3 33 NA 1 0
We can mutate only the columns beginning with i followed by a number using across and matches from dplyr and we can change values as you've specified using recode.
library(dplyr)
df %>%
mutate(across(matches('^i\\d+'), recode, '1' = 0, '0' = 1))
Alternatively, in base R you can do this
i_cols <- str_detect(colnames(df), '^i\\d+')
df[,i_cols] <- ifelse(df[,i_cols] == 0, 1, 0)
