GitHub - tidyverse/dplyr: dplyr: A grammar of data manipulation (original) (raw)

dplyr

Overview

dplyr is a grammar of data manipulation, providing a consistent set of verbs that help you solve the most common data manipulation challenges:

• mutate() adds new variables that are functions of existing variables
• select() picks variables based on their names.
• filter() picks cases based on their values.
• summarise() reduces multiple values down to a single summary.
• arrange() changes the ordering of the rows.

These all combine naturally with group_by() which allows you to perform any operation “by group”. You can learn more about them invignette("dplyr"). As well as these single-table verbs, dplyr also provides a variety of two-table verbs, which you can learn about invignette("two-table").

If you are new to dplyr, the best place to start is the data transformation chapter in R for Data Science.

Backends

In addition to data frames/tibbles, dplyr makes working with other computational backends accessible and efficient. Below is a list of alternative backends:

• arrow for larger-than-memory datasets, including on remote cloud storage like AWS S3, using the Apache Arrow C++ engine,Acero.
• dtplyr for large, in-memory datasets. Translates your dplyr code to high performancedata.table code.
• dbplyr for data stored in a relational database. Translates your dplyr code to SQL.
• duckplyr for usingduckdb on large, in-memory datasets with zero extra copies. Translates your dplyr code to high performance duckdb queries with an automatic R fallback when translation isn’t possible.
• duckdb for large datasets that are still small enough to fit on your computer.
• sparklyr for very large datasets stored in Apache Spark.

Installation

The easiest way to get dplyr is to install the whole tidyverse:

install.packages("tidyverse")

Alternatively, install just dplyr:

install.packages("dplyr")

Development version

To get a bug fix or to use a feature from the development version, you can install the development version of dplyr from GitHub.

install.packages("pak")

pak::pak("tidyverse/dplyr")

Cheat Sheet

Usage

library(dplyr)

starwars %>% filter(species == "Droid") #> # A tibble: 6 × 14 #> name height mass hair_color skin_color eye_color birth_year sex gender
#>
#> 1 C-3PO 167 75 gold yellow 112 none masculi… #> 2 R2-D2 96 32 white, blue red 33 none masculi… #> 3 R5-D4 97 32 white, red red NA none masculi… #> 4 IG-88 200 140 none metal red 15 none masculi… #> 5 R4-P17 96 NA none silver, red red, blue NA none feminine #> # ℹ 1 more row #> # ℹ 5 more variables: homeworld , species , films , #> # vehicles , starships

starwars %>% select(name, ends_with("color")) #> # A tibble: 87 × 4 #> name hair_color skin_color eye_color #>
#> 1 Luke Skywalker blond fair blue
#> 2 C-3PO gold yellow
#> 3 R2-D2 white, blue red
#> 4 Darth Vader none white yellow
#> 5 Leia Organa brown light brown
#> # ℹ 82 more rows

starwars %>% mutate(name, bmi = mass / ((height / 100) ^ 2)) %>% select(name:mass, bmi) #> # A tibble: 87 × 4 #> name height mass bmi #> #> 1 Luke Skywalker 172 77 26.0 #> 2 C-3PO 167 75 26.9 #> 3 R2-D2 96 32 34.7 #> 4 Darth Vader 202 136 33.3 #> 5 Leia Organa 150 49 21.8 #> # ℹ 82 more rows

starwars %>% arrange(desc(mass)) #> # A tibble: 87 × 14 #> name height mass hair_color skin_color eye_color birth_year sex gender #> #> 1 Jabba De… 175 1358 green-tan… orange 600 herm… mascu… #> 2 Grievous 216 159 none brown, wh… green, y… NA male mascu… #> 3 IG-88 200 140 none metal red 15 none mascu… #> 4 Darth Va… 202 136 none white yellow 41.9 male mascu… #> 5 Tarfful 234 136 brown brown blue NA male mascu… #> # ℹ 82 more rows #> # ℹ 5 more variables: homeworld , species , films , #> # vehicles , starships

starwars %>% group_by(species) %>% summarise( n = n(), mass = mean(mass, na.rm = TRUE) ) %>% filter( n > 1, mass > 50 ) #> # A tibble: 9 × 3 #> species n mass #> #> 1 Droid 6 69.8 #> 2 Gungan 3 74
#> 3 Human 35 81.3 #> 4 Kaminoan 2 88
#> 5 Mirialan 2 53.1 #> # ℹ 4 more rows

Getting help

If you encounter a clear bug, please file an issue with a minimal reproducible example onGitHub. For questions and other discussion, please use forum.posit.co.

Code of conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.