dplyr::relocate()

Function of the Week: dplyr::relocate()

`relocate()`

In this document, I will introduce the relocate() function from dplyr and show what it’s for.

#load tidyverse up
library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

## ✓ ggplot2 3.3.5     ✓ purrr   0.3.4
## ✓ tibble  3.1.6     ✓ dplyr   1.0.7
## ✓ tidyr   1.1.4     ✓ stringr 1.4.0
## ✓ readr   2.1.1     ✓ forcats 0.5.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(gt)
#example dataset
library(palmerpenguins)
data(penguins)

What is it for?

The relocate() function is used to change the order of columns in a dataframe. This can be done in a few different ways.

Arguments are the data frame, followed by the column(s) to be moved, then the new position.

Move one column

If a new position is not specified, the default is to move the column to the first position. This can be used to move one or more columns. Use .before or .after to designate the new column position.

penguins %>% 
  head() %>% gt()

species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adelie	Torgersen	39.1	18.7	181	3750	male	2007
Adelie	Torgersen	39.5	17.4	186	3800	female	2007
Adelie	Torgersen	40.3	18.0	195	3250	female	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	36.7	19.3	193	3450	female	2007
Adelie	Torgersen	39.3	20.6	190	3650	male	2007

penguins %>% 
  relocate(year, bill_depth_mm) %>% 
  head() %>% gt()

year	bill_depth_mm	species	island	bill_length_mm	flipper_length_mm	body_mass_g	sex
2007	18.7	Adelie	Torgersen	39.1	181	3750	male
2007	17.4	Adelie	Torgersen	39.5	186	3800	female
2007	18.0	Adelie	Torgersen	40.3	195	3250	female
2007	NA	Adelie	Torgersen	NA	NA	NA	NA
2007	19.3	Adelie	Torgersen	36.7	193	3450	female
2007	20.6	Adelie	Torgersen	39.3	190	3650	male

penguins %>% 
  relocate(year, .after = island) %>% 
  head() %>% gt()

species	island	year	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex
Adelie	Torgersen	2007	39.1	18.7	181	3750	male
Adelie	Torgersen	2007	39.5	17.4	186	3800	female
Adelie	Torgersen	2007	40.3	18.0	195	3250	female
Adelie	Torgersen	2007	NA	NA	NA	NA	NA
Adelie	Torgersen	2007	36.7	19.3	193	3450	female
Adelie	Torgersen	2007	39.3	20.6	190	3650	male

# or
relocate(penguins, year, .after = island) %>% 
  head() %>% gt()

species	island	year	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex
Adelie	Torgersen	2007	39.1	18.7	181	3750	male
Adelie	Torgersen	2007	39.5	17.4	186	3800	female
Adelie	Torgersen	2007	40.3	18.0	195	3250	female
Adelie	Torgersen	2007	NA	NA	NA	NA	NA
Adelie	Torgersen	2007	36.7	19.3	193	3450	female
Adelie	Torgersen	2007	39.3	20.6	190	3650	male

Move a block of columns

Similar to functions like select(), a block of columns can be chosen.

penguins %>% 
  head() %>% gt()

species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adelie	Torgersen	39.1	18.7	181	3750	male	2007
Adelie	Torgersen	39.5	17.4	186	3800	female	2007
Adelie	Torgersen	40.3	18.0	195	3250	female	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	36.7	19.3	193	3450	female	2007
Adelie	Torgersen	39.3	20.6	190	3650	male	2007

penguins %>% 
  relocate(body_mass_g:year, .before = bill_length_mm) %>% 
  head() %>% gt()

species	island	body_mass_g	sex	year	bill_length_mm	bill_depth_mm	flipper_length_mm
Adelie	Torgersen	3750	male	2007	39.1	18.7	181
Adelie	Torgersen	3800	female	2007	39.5	17.4	186
Adelie	Torgersen	3250	female	2007	40.3	18.0	195
Adelie	Torgersen	NA	NA	2007	NA	NA	NA
Adelie	Torgersen	3450	female	2007	36.7	19.3	193
Adelie	Torgersen	3650	male	2007	39.3	20.6	190

Move using `tidyselect` helpers

penguins %>% 
  head() %>% gt()

species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adelie	Torgersen	39.1	18.7	181	3750	male	2007
Adelie	Torgersen	39.5	17.4	186	3800	female	2007
Adelie	Torgersen	40.3	18.0	195	3250	female	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	36.7	19.3	193	3450	female	2007
Adelie	Torgersen	39.3	20.6	190	3650	male	2007

penguins %>% 
  relocate(contains("_mm"), .after = species) %>% 
  head() %>% gt()

species	bill_length_mm	bill_depth_mm	flipper_length_mm	island	body_mass_g	sex	year
Adelie	39.1	18.7	181	Torgersen	3750	male	2007
Adelie	39.5	17.4	186	Torgersen	3800	female	2007
Adelie	40.3	18.0	195	Torgersen	3250	female	2007
Adelie	NA	NA	NA	Torgersen	NA	NA	2007
Adelie	36.7	19.3	193	Torgersen	3450	female	2007
Adelie	39.3	20.6	190	Torgersen	3650	male	2007

Move columns based on their type

Another handy option is to rearrange the columns based on the type of data. The penguins dataset contains both factors and numbers.

penguins %>% 
  head() %>% gt()

species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adelie	Torgersen	39.1	18.7	181	3750	male	2007
Adelie	Torgersen	39.5	17.4	186	3800	female	2007
Adelie	Torgersen	40.3	18.0	195	3250	female	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	36.7	19.3	193	3450	female	2007
Adelie	Torgersen	39.3	20.6	190	3650	male	2007

penguins %>% 
  relocate(where(is.numeric), .after = where(is.factor)) %>% 
  head() %>% gt()

species	island	sex	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	year
Adelie	Torgersen	male	39.1	18.7	181	3750	2007
Adelie	Torgersen	female	39.5	17.4	186	3800	2007
Adelie	Torgersen	female	40.3	18.0	195	3250	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	female	36.7	19.3	193	3450	2007
Adelie	Torgersen	male	39.3	20.6	190	3650	2007

Bonus: Rename

An additional feature of this function is the ability to rename columns. Again, the default is to move the renamed column to the first position in the dataframe. This is easily addressed by specifying the position with .before or .after. This is a nice option if you want to move a column and rename it all at once.

penguins %>% 
  head() %>% gt()

species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adelie	Torgersen	39.1	18.7	181	3750	male	2007
Adelie	Torgersen	39.5	17.4	186	3800	female	2007
Adelie	Torgersen	40.3	18.0	195	3250	female	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	36.7	19.3	193	3450	female	2007
Adelie	Torgersen	39.3	20.6	190	3650	male	2007

penguins %>% 
  relocate(site = island) %>% 
  head() %>% gt()

site	species	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Torgersen	Adelie	39.1	18.7	181	3750	male	2007
Torgersen	Adelie	39.5	17.4	186	3800	female	2007
Torgersen	Adelie	40.3	18.0	195	3250	female	2007
Torgersen	Adelie	NA	NA	NA	NA	NA	2007
Torgersen	Adelie	36.7	19.3	193	3450	female	2007
Torgersen	Adelie	39.3	20.6	190	3650	male	2007

penguins %>% 
  relocate(site = island, .after = species) %>% 
  head() %>% gt()

species	site	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adelie	Torgersen	39.1	18.7	181	3750	male	2007
Adelie	Torgersen	39.5	17.4	186	3800	female	2007
Adelie	Torgersen	40.3	18.0	195	3250	female	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	36.7	19.3	193	3450	female	2007
Adelie	Torgersen	39.3	20.6	190	3650	male	2007

Is it helpful?

This is a very useful function, especially with large dataframes with many columns. It is also very useful when new columns are added and need to be placed in specific positions. relocate() allows you to easily rearrange columns to better display the data for presentation and analysis.

Last updated on February 28, 2022

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dplyr::relocate()

Function of the Week: dplyr::relocate()

Trisha Marsh

2022-02-23

`relocate()`

What is it for?

Move one column

Move a block of columns

Move using `tidyselect` helpers

Move columns based on their type

Bonus: Rename

Is it helpful?

dplyr::relocate()

Function of the Week: dplyr::relocate()

Trisha Marsh

2022-02-23

relocate()

What is it for?

Move one column

Move a block of columns

Move using tidyselect helpers

Move columns based on their type

Bonus: Rename

Is it helpful?

`relocate()`

Move using `tidyselect` helpers