Column Names As Parameters

I always forget how to use column names as function parameters, so here is an example.

Function with no column name parameters

Function:

library(tidyverse)

dish <- data.frame(
  'person' = c('jimmy', 'james', 'johnny'),
  'v_1' = c(rnorm(3, 0, 1)),
  'v_2' = c(rnorm(3, 10, 5)),
  'v_3' = c(rnorm(3, 50, 10)),
  'v_4' = c(rnorm(3, 25, 15))
)

mini <- dish %>%
  select(person, v_1, v_2)

mini[mini$person == 'jimmy', 2] <- 99
mini[mini$person == 'james', 2] <- 99

The original data:

  person        v_1       v_2      v_3      v_4
1  jimmy  0.4543694 14.593479 62.66191 10.95676
2  james -0.4837649 10.126899 48.31108 23.01771
3 johnny -0.9562436  6.407953 49.09710 26.37863

What we changed it to:

  person        v_1       v_2
1  jimmy 99.0000000 14.593479
2  james 99.0000000 10.126899
3 johnny -0.9562436  6.407953

Here is the function equivalent:

impute_99 <- function(data){
  
  
  new_data <- data %>%
    select(person, v_1, v_2)
  
  new_data[new_data$person == 'jimmy', 2] <- 99
  new_data[new_data$person == 'james', 2] <- 99
  
  return(new_data)
  
  
}

Our result:

adjusted_data <- impute_99(dish)
adjusted_data

  person        v_1       v_2
1  jimmy 99.0000000 14.593479
2  james 99.0000000 10.126899
3 johnny -0.9562436  6.407953

Function with column names as parameters

Now, what if we want to use specific column names as parameters in our function? We could change the function to:

impute_99_column_specific <- function(data, column1, column2){
  
  new_data <- data %>%
    select(person, column1, column2)
  
  new_data[new_data$person == 'jimmy', 2] <- 99 # column1 change
  new_data[new_data$person == 'james', 2] <- 99 # column2 change
  
  return(new_data)
  
}

where ‘column1’ and ‘column2’ can be replaced by specific names. Here is where I usually get confused, the following code does not work:

cool_data <- impute_99_column_specific(dish, v_1, v_2)

Fortunately the correction is simple, just put quotes around the column names:

cool_data <- impute_99_column_specific(dish, 'v_1', 'v_2')
cool_data

  person        v_1       v_2
1  jimmy 99.0000000 14.593479
2  james 99.0000000 10.126899
3 johnny -0.9562436  6.407953

Bo\(^2\)m =)