In this post we will learn how to change column order or move a column in R with dplyr. More specifically, we will learn how to move a single column of interest to first in the dataframe, before and after a specific column in the dataframe. We will use relocate() function available in dplyr version 1.0.0 to change the column position.
Let us load tidyverse first.
library("tidyverse")
As in other tidyverse 101 examples, we will use the fantastic Penguins dataset to illustrate the three ways to see data in a dataframe. Let us load the data from cmdlinetips.com’ github page.
path2data <- "https://raw.githubusercontent.com/cmdlinetips/data/master/palmer_penguins.csv" penguins<- readr::read_csv(path2data)
Note that the last column in the data frame is sex column.
## Parsed with column specification: ## cols( ## species = col_character(), ## island = col_character(), ## bill_length_mm = col_double(), ## bill_depth_mm = col_double(), ## flipper_length_mm = col_double(), ## body_mass_g = col_double(), ## sex = col_character() ## )
First, we will see how to move a column to first in the dataframe. To move a column to first in the dataframe, we use relocate() with the column name we want to move.
penguins %>% relocate(sex)
This will move the column of interest to the first column.
## # A tibble: 344 x 7 ## sex species island bill_length_mm bill_depth_mm flipper_length_… ## <chr> <chr> <chr> <dbl> <dbl> <dbl> ## 1 male Adelie Torge… 39.1 18.7 181 ## 2 fema… Adelie Torge… 39.5 17.4 186 ## 3 fema… Adelie Torge… 40.3 18 195 ## 4 <NA> Adelie Torge… NA NA NA ## 5 fema… Adelie Torge… 36.7 19.3 193 ## 6 male Adelie Torge… 39.3 20.6 190 ## 7 fema… Adelie Torge… 38.9 17.8 181 ## 8 male Adelie Torge… 39.2 19.6 195 ## 9 <NA> Adelie Torge… 34.1 18.1 193 ## 10 <NA> Adelie Torge… 42 20.2 190 ## # … with 334 more rows, and 1 more variable: body_mass_g <dbl>
We can also move the column of interest to a location after another column in the dataframe. In this example, we move the column “sex” to position after “species” column.
penguins %>% relocate(sex, .after=species)
Notice that now the sex column is second column after the species.
## # A tibble: 344 x 7 ## species sex island bill_length_mm bill_depth_mm flipper_length_… ## <chr> <chr> <chr> <dbl> <dbl> <dbl> ## 1 Adelie male Torge… 39.1 18.7 181 ## 2 Adelie fema… Torge… 39.5 17.4 186 ## 3 Adelie fema… Torge… 40.3 18 195 ## 4 Adelie <NA> Torge… NA NA NA ## 5 Adelie fema… Torge… 36.7 19.3 193 ## 6 Adelie male Torge… 39.3 20.6 190 ## 7 Adelie fema… Torge… 38.9 17.8 181 ## 8 Adelie male Torge… 39.2 19.6 195 ## 9 Adelie <NA> Torge… 34.1 18.1 193 ## 10 Adelie <NA> Torge… 42 20.2 190 ## # … with 334 more rows, and 1 more variable: body_mass_g <dbl>
Similarly we can also specify the location to be after another column present in the dataframe. In this example, we move sex column to be relocated after “bill_length_mm”.
penguins %>% relocate(sex, .before=bill_length_mm)
## # A tibble: 344 x 7 ## species island sex bill_length_mm bill_depth_mm flipper_length_… ## <chr> <chr> <chr> <dbl> <dbl> <dbl> ## 1 Adelie Torge… male 39.1 18.7 181 ## 2 Adelie Torge… fema… 39.5 17.4 186 ## 3 Adelie Torge… fema… 40.3 18 195 ## 4 Adelie Torge… <NA> NA NA NA ## 5 Adelie Torge… fema… 36.7 19.3 193 ## 6 Adelie Torge… male 39.3 20.6 190 ## 7 Adelie Torge… fema… 38.9 17.8 181 ## 8 Adelie Torge… male 39.2 19.6 195 ## 9 Adelie Torge… <NA> 34.1 18.1 193 ## 10 Adelie Torge… <NA> 42 20.2 190 ## # … with 334 more rows, and 1 more variable: body_mass_g <dbl>
In this post, we saw how to move a single column to first and before or after another column. dplyr’s relocate() is versatile and can conditions as input to move multiple columns at the same time. Check out soon for more examples of using dplyr’s relocate().
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