36 rename
Written by Mariam Walaa and last updated on 7 October 2021.
36.1 Introduction
In this lesson, you will learn how to:
- Rename columns in a data frame
Prerequisite skills include:
- Using the pipe %>% operator
Highlights:
36.2 Arguments
The rename() function takes the following as arguments:
| Argument | Parameter | Details |
|---|---|---|
| x | object | this is the data with variables to rename (typically a data frame) |
| replace | vector | this takes a vector as c(new_name = old_name) |
You can read more about the arguments in the rename() function documentation
here.
36.3 Overview
Sometimes we have to work with data sets with columns that are difficult to understand or
work with. In this case, we can rename the columns using the rename() function.
In this tutorial, we will be using a data set about fictional character personalities for
reference. This data set already consists of simple, clear, and well-named variables, but
we are going to try to simplify them even further using rename().
We will start by loading the data from GitHub.
We will also load the personalities dataset.
personalities <- read_tsv(
"https://raw.githubusercontent.com/tacookson/data/master/fictional-character-personalities/personalities.txt")
#> Rows: 213600 Columns: 11
#> ── Column specification ────────────────────────────────────
#> Delimiter: "\t"
#> chr (7): character_code, fictional_work, character_name,...
#> dbl (3): mean, ratings, sd
#> lgl (1): is_emoji
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Here is the dataset. This data consists of 213,600 rows, each representing a fictional character, and 11 columns describing the character and their personality.
glimpse(personalities)
#> Rows: 213,600
#> Columns: 11
#> $ character_code <chr> "A/4", "A/4", "A/4", "A/4", "A/4", …
#> $ fictional_work <chr> "Alien", "Alien", "Alien", "Alien",…
#> $ character_name <chr> "Ash", "Ash", "Ash", "Ash", "Ash", …
#> $ gender <chr> "male", "male", "male", "male", "ma…
#> $ spectrum <chr> "BAP1", "BAP2", "BAP3", "BAP4", "BA…
#> $ spectrum_low <chr> "playful", "shy", "cheery", "mascul…
#> $ spectrum_high <chr> "serious", "bold", "sorrowful", "fe…
#> $ is_emoji <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, …
#> $ mean <dbl> 41.4, 11.1, 22.4, -16.9, 23.1, 3.8,…
#> $ ratings <dbl> 51, 63, 78, 71, 72, 60, 76, 74, 72,…
#> $ sd <dbl> 10.9, 27.3, 14.0, 22.3, 25.2, 32.9,…We can see that the first three columns are about the character unique ID, the fictional work that they are from, and their name. To demonstrate the use of the rename function, we will rename each of these three variables to one word each.
personalities <- personalities %>%
rename(id = character_code,
work = fictional_work,
name = character_name)We have renamed 3 columns in the data frame and re-assigned it to personalities.
glimpse(personalities)
#> Rows: 213,600
#> Columns: 11
#> $ id <chr> "A/4", "A/4", "A/4", "A/4", "A/4", "…
#> $ work <chr> "Alien", "Alien", "Alien", "Alien", …
#> $ name <chr> "Ash", "Ash", "Ash", "Ash", "Ash", "…
#> $ gender <chr> "male", "male", "male", "male", "mal…
#> $ spectrum <chr> "BAP1", "BAP2", "BAP3", "BAP4", "BAP…
#> $ spectrum_low <chr> "playful", "shy", "cheery", "masculi…
#> $ spectrum_high <chr> "serious", "bold", "sorrowful", "fem…
#> $ is_emoji <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, F…
#> $ mean <dbl> 41.4, 11.1, 22.4, -16.9, 23.1, 3.8, …
#> $ ratings <dbl> 51, 63, 78, 71, 72, 60, 76, 74, 72, …
#> $ sd <dbl> 10.9, 27.3, 14.0, 22.3, 25.2, 32.9, …Now we have a data frame with renamed columns.
What if we have a column that does not have a name? We can still name it by indexing the
column using base R function names().
personalities %>%
rename(fictional_work = names(.)[2])
#> # A tibble: 213,600 × 11
#> id fictional_work name gender spectrum spectrum_low
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 A/4 Alien Ash male BAP1 playful
#> 2 A/4 Alien Ash male BAP2 shy
#> 3 A/4 Alien Ash male BAP3 cheery
#> 4 A/4 Alien Ash male BAP4 masculine
#> 5 A/4 Alien Ash male BAP5 charming
#> 6 A/4 Alien Ash male BAP6 lewd
#> 7 A/4 Alien Ash male BAP7 intellectual
#> 8 A/4 Alien Ash male BAP8 strict
#> 9 A/4 Alien Ash male BAP9 refined
#> 10 A/4 Alien Ash male BAP10 trusting
#> # … with 213,590 more rows, and 5 more variables:
#> # spectrum_high <chr>, is_emoji <lgl>, mean <dbl>,
#> # ratings <dbl>, sd <dbl>Here, we change the work column back to fictional_work simply by indexing the second column in the personalities data frame. This column already had a name, but if it did not, this method would have still successfully named it to fictional_work.
36.5 Common Mistakes & Errors
Below are some common mistakes and errors you may come across:
- You pass the old name first instead of the new name. The syntax requires passing the new column name, followed by an equal sign, and then the old column name.
- You are not correctly typing the name.
- You are not using the correct quotation marks. For example, if you have whitespace between words in the column name, you need to use `` as opposed to the other quotation marks.
If you have other issues, check that you have loaded tidyverse or dplyr into your session! Remember that a lot of issues can come from not loading the required packages.
36.6 Next Steps
If you would like to read more about the rename() function, here are some additional
resources you may find helpful: