CODEWITHSUNDEEP
r
zucchini
zucchini

Reputation: 33

How to rename multiple variables at once?

I have multiple columns with variables I need to reverse-code. Let's say my column names are A,B,C,D and each column has a mix of values from 1-4. I am trying to recode all the 4's as 1's, 3's as 2's. etc.

I am able to do it like this:

`dataNew$A <- as.numeric(dataNew$A)
levels(dataNew$A)[levels(dataNew$A)=="1"] <- "4"
levels(dataNew$A)[levels(dataNew$A)=="2"] <- "3"
levels(dataNew$A)[levels(dataNew$A)=="3"] <- "2"
levels(dataNew$A)[levels(dataNew$A)=="2"] <- "1"`

Then I could repeat for columns B, C, D

However, I'm wondering if there is a cleaner way to do this where I can change multiple numbers or multiple columns and numbers at once, rather than individually writing the above code for each column/number combination.

Upvotes: 1

Views: 552

Answers (2)

caldwellst
caldwellst

Reputation: 5956

If those are the only data frame values, then you can actually do something very simple, stealing @Michael Dewar's sample data code.

df <- data.frame(
  A = sample(1:4, 50, replace = TRUE),
  B = sample(1:4, 50, replace = TRUE),
  C = sample(1:4, 50, replace = TRUE),
  D = sample(1:4, 50, replace = TRUE)
)

head(df)
#>   A B C D
#> 1 3 4 4 3
#> 2 2 3 3 1
#> 3 1 4 1 2
#> 4 4 1 2 1
#> 5 4 3 3 2
#> 6 1 2 2 1

df <- 5 - df
head(df)
#>   A B C D
#> 1 2 1 1 2
#> 2 3 2 2 4
#> 3 4 1 4 3
#> 4 1 4 3 4
#> 5 1 2 2 3
#> 6 4 3 3 4

If your newData is not numeric and you want to convert, you can easily convert into a numeric data frame using:

as.data.frame(sapply(newData, as.numeric))

However, since it appears your data might be factors, you should be careful how those are converted to as.numeric. See this thread for the details, but you might want to do:

as.data.frame(sapply(newData, \(x) as.numeric(levels(x)[x])))

Upvotes: 3

Michael Dewar
Michael Dewar

Reputation: 3318

How about:

library(tidyverse)

dataNew <- tibble(A = sample(1:4, 50, replace = TRUE),
                  B = sample(1:4, 50, replace = TRUE),
                  C = sample(1:4, 50, replace = TRUE),
                  D = sample(1:4, 50, replace = TRUE))
dataNew %>% 
    mutate(across(A:D, ~ 5-.))

Upvotes: 3

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