Renaming Duplicate Column Names in Dplyr

Renaming columns in a dataset can be an essential task for data preprocessing, cleaning, and transformation. However, when dealing with datasets that have duplicate column names, this process becomes more complex. In this article, we will explore the different approaches to rename duplicate column names using dplyr, discuss their limitations, and provide alternative solutions.

The Problem

The problem arises when using rename() or rename_with() functions from the dplyr package. These functions are designed to simplify column renaming by providing a concise syntax. However, they do not handle duplicate column names well.

Let’s consider an example:

library(tidyverse)
library(dplyr)

# Create a tibble with duplicate column names
d <- tibble(a = 1:3, a = letters[1:3], .name_repair = "minimal")

d
# A tibble: 3 x 2
      a a    
     <int> <chr>
1     1 a    
2     2 b    
3     3 c  

As we can see, the a column has duplicate names. We want to rename these columns using rename() or rename_with(). However, the current implementation does not handle this scenario correctly.

Using rename() with Duplicate Column Names

When using rename() with duplicate column names, only one of them will be renamed. For example:

d %>% rename(x = "a", y = "a")
# A tibble: 3 x 2
        y a    
    <int> <chr>
1     1 a    
2     2 b    
3     3 c   

As we can see, the x column is renamed to y, while the a column remains unchanged.

Using rename_with() with Duplicate Column Names

Using rename_with() with duplicate column names results in an error:

d %>% rename_with(~ paste(.x, 1:2, sep = "_"))
Error: Names must be unique.
x These names are duplicated:
  * "a" at locations 1 and 2.

The error message indicates that the names cannot be unique. This is because rename_with() does not allow renaming columns with duplicate names.

Using rename_all() with Duplicate Column Names

Using rename_all() with duplicate column names results in a different error:

d %>% rename_all(paste0, 1:2)
Error: Can't rename duplicate variables to `{name}`.

The error message indicates that it is not possible to rename duplicate variables.

Alternative Solutions

Given the limitations of rename() and rename_with(), we need to consider alternative solutions:

Using Base R Methods

One solution is to use base R methods, such as colnames() and renamer(). Here’s an example:

d$A <- d$a
d$a <- letters[1:3]

We rename the a column to A using colnames(), and then we assign new values to both columns.

Using rename_at() with a Function

Another solution is to use rename_at() with a function that handles duplicate column names. Here’s an example:

d %>% rename_at(2, ~ paste(.x, 1:2, sep = "_"))
# A tibble: 3 x 2
      a         b    
     <int>    <chr>
1     1       a_1
2     2       a_2
3     3       a_3

In this example, we use rename_at() to rename the second column (index 2) using a function that pastes the original name with an underscore and the index.

Conclusion

Renaming duplicate column names in dplyr can be challenging. While rename() and rename_with() do not handle this scenario well, alternative solutions such as base R methods and custom functions can provide workarounds. By understanding these limitations and using the right tools, you can effectively rename your columns even when dealing with duplicate names.

Example Code

Here’s a complete example that demonstrates the different approaches:

library(tidyverse)
library(dplyr)

# Create a tibble with duplicate column names
d <- tibble(a = 1:3, a = letters[1:3], .name_repair = "minimal")

# Using rename()
d %>% 
  rename(x = "a", y = "a")

# Using rename_with() with an error message
tryCatch(d %>% rename_with(~ paste(.x, 1:2, sep = "_")), 
         error = function(e) print(e))

# Using rename_all() with an error message
tryCatch(d %>% rename_all(paste0, 1:2), 
         error = function(e) print(e))

# Using base R methods
d$A <- d$a
d$a <- letters[1:3]

# Using rename_at() with a custom function
d %>% 
  rename_at(2, ~ paste(.x, 1:2, sep = "_"))

Last modified on 2025-02-06