Introduction to function in R - Renaming modalities of multiple logical variables

[Thibaud]

Hey there,

The idea would be to modify each modality of a list of variable (determined) of a dataframe from 0 to "NO" and from 1 to "YES". I already know how to do that for one variable at a time ... :

Id               <- c("345","346","347","349","350")
Binary_Variable1 <- c(0,0,0,1,0)

df <- data.frame(Id,Binary_Variable1)

df<-df |>
  mutate(Binary_Variable1 = factor(case_when(
    Binary_Variable1== "0"     ~ "Non",
    Binary_Variable1 == "1"     ~ "Oui",
    TRUE ~ NA_character_)
  )
  )

... And I would like to create an easy function able to do so for multiple variable at once beacause my dataframe is really large

### Create a random dataframe 

Id               <- c("345","346","347","349","350")
Binary_Variable1 <- c(0,0,0,1,0)
Binary_Variable2 <- c(1,0,1,1,0)
Binary_Variable3 <- c(1,1,1,1,1)
Binary_Variable4 <- c(0,1,0,1,1)

df <- data.frame(Id, Binary_Variable1, Binary_Variable2, Binary_Variable3, Binary_Variable4)

### Create the function 


Renomm_Variables_Binaire <- function(data_frame_source,vecteurs_variables){
 
  for  (vecteurs_variables in data_frame_source) {
    
    data_frame_source<-data_frame_source |>
      mutate(i = factor(case_when(
        i == "0"     ~ "Non",
        i == "1"     ~ "Oui",
        TRUE ~ NA_character_)
        }} 





###  Use it to change all 0 into 'No' and 1 to "Yes"

vector<- df %>%  select(Binary_Variable1,Binary_Variable2,Binary_Variable3,Binary_Variable4)

Renomm_Variables_Binaire(df,vector)

I know there are some mistakes to my function because it refuses to work...

By the way, do you know any R package that helps you design your own function ?

Thank you very much in advance !

[fcas80]

Here is a non-function approach:

Id <- c("345","346","347","349","350")
Binary_Variable1 <- c(0,0,0,1,0)
Binary_Variable2 <- c(1,0,1,1,0)
Binary_Variable3 <- c(1,1,1,1,1)
Binary_Variable4 <- c(0,1,0,1,1)

df <- data.frame(Id, Binary_Variable1, Binary_Variable2, Binary_Variable3, Binary_Variable4)
df <- ifelse(df[, 2:5] == 0, "Non", "Oui")
df

Note that I don't want to change column 1.

[nirgrahamuk]

dplyr has an across function meant to help with mutate/summarise

library(tidyverse)

df <- tibble::tribble(
  ~Id, ~Binary_Variable1, ~Binary_Variable2, ~Binary_Variable3, ~Binary_Variable4,
  "345",                 0,                 1,                 1,                 0,
  "346",                 0,                 0,                 1,                 1,
  "347",                 0,                 1,                 1,                 0,
  "349",                 1,                 1,                 1,                 1,
  "350",                 0,                 0,                 1,                 1
)

mutate(df,
       across(.cols = starts_with("Binary"),
              .fns = ~case_when(.x==0 ~ 'No',
                                .x==1 ~ 'Yes',
                                NA ~ NA_character_)))

[Thibaud]

@nirgrahamuk

library(tidyverse)

df <- tibble::tribble(
  ~Id, ~Binary_Variable1, ~Binary_Variable2, ~Binary_Variable3, ~Binary_Variable4,
  "345",                 0,                 1,                 1,                 0,
  "346",                 0,                 0,                 1,                 1,
  "347",                 0,                 1,                 1,                 0,
  "349",                 1,                 1,                 1,                 1,
  "350",                 0,                 0,                 1,                 1
)

mutate(df,
       across(.cols = starts_with("Binary"),
              .fns = ~case_when(.x==0 ~ 'No',
                                .x==1 ~ 'Yes',
                                NA ~ NA_character_)))

Thanks for your answer ! More useful than the other one (which work also ) in case of large dataset ! Thanks !