dplyr::slice()

Ted Laderas

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

library(tidyverse)

## Warning: package 'tidyverse' was built under R version 4.0.3

## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --

## v ggplot2 3.3.3     v purrr   0.3.4
## v tibble  3.0.6     v dplyr   1.0.4
## v tidyr   1.1.2     v stringr 1.4.0
## v readr   1.4.0     v forcats 0.5.1

## Warning: package 'ggplot2' was built under R version 4.0.3

## Warning: package 'tibble' was built under R version 4.0.3

## Warning: package 'tidyr' was built under R version 4.0.3

## Warning: package 'readr' was built under R version 4.0.3

## Warning: package 'purrr' was built under R version 4.0.3

## Warning: package 'dplyr' was built under R version 4.0.3

## Warning: package 'stringr' was built under R version 4.0.3

## Warning: package 'forcats' was built under R version 4.0.3

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

library(palmerpenguins)

## Warning: package 'palmerpenguins' was built under R version 4.0.3

data(penguins)

What is it for?

Say you want the first 7 rows of a table. Well, slice() is an easy way to do that. The slice() function accepts two arguments: The first is the dataset, and the second is the range of values you want to extract.

slice(penguins, 1:7)

## # A tibble: 7 x 8
##   species island bill_length_mm bill_depth_mm flipper_length_~ body_mass_g sex  
##   <fct>   <fct>           <dbl>         <dbl>            <int>       <int> <fct>
## 1 Adelie  Torge~           39.1          18.7              181        3750 male 
## 2 Adelie  Torge~           39.5          17.4              186        3800 fema~
## 3 Adelie  Torge~           40.3          18                195        3250 fema~
## 4 Adelie  Torge~           NA            NA                 NA          NA <NA> 
## 5 Adelie  Torge~           36.7          19.3              193        3450 fema~
## 6 Adelie  Torge~           39.3          20.6              190        3650 male 
## 7 Adelie  Torge~           38.9          17.8              181        3625 fema~
## # ... with 1 more variable: year <int>

slice() is much more helpful in a tidy workflow, so you can see the first few rows of the data when you’re processing. This is really helpful when you’re building up a pipeline and need to show intermediate output without showing the entire table.

penguins %>%
  slice(1:7)

## # A tibble: 7 x 8
##   species island bill_length_mm bill_depth_mm flipper_length_~ body_mass_g sex  
##   <fct>   <fct>           <dbl>         <dbl>            <int>       <int> <fct>
## 1 Adelie  Torge~           39.1          18.7              181        3750 male 
## 2 Adelie  Torge~           39.5          17.4              186        3800 fema~
## 3 Adelie  Torge~           40.3          18                195        3250 fema~
## 4 Adelie  Torge~           NA            NA                 NA          NA <NA> 
## 5 Adelie  Torge~           36.7          19.3              193        3450 fema~
## 6 Adelie  Torge~           39.3          20.6              190        3650 male 
## 7 Adelie  Torge~           38.9          17.8              181        3625 fema~
## # ... with 1 more variable: year <int>

Is it helpful?

Yes, when you need to just show part of a table as an example, slice() can come in handy. I don’t use it everyday, but it can come in handy.