README.md

dplyr

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Overview

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

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

dplyr is designed to abstract over how the data is stored. That means as well as working with local data frames, you can also work with remote database tables, using exactly the same R code. Install the dbplyr package then read vignette("databases", package = "dbplyr").

If you are new to dplyr, the best place to start is the data import chapter in R for data science.

Installation

# The easiest way to get dplyr is to install the whole tidyverse:
install.packages("tidyverse")

# Alternatively, install just dplyr:
install.packages("dplyr")

# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("tidyverse/dplyr")

If you encounter a clear bug, please file a minimal reproducible example on github. For questions and other discussion, please use the manipulatr mailing list.

Usage

library(dplyr)

starwars %>% 
  filter(species == "Droid")
#> # A tibble: 5 x 13
#>   name  height  mass hair_color skin_color  eye_color birth_year gender
#>   <chr>  <int> <dbl> <chr>      <chr>       <chr>          <dbl> <chr> 
#> 1 C-3PO    167   75. <NA>       gold        yellow          112. <NA>  
#> 2 R2-D2     96   32. <NA>       white, blue red              33. <NA>  
#> 3 R5-D4     97   32. <NA>       white, red  red              NA  <NA>  
#> 4 IG-88    200  140. none       metal       red              15. none  
#> 5 BB8       NA   NA  none       none        black            NA  none  
#> # ... with 5 more variables: homeworld <chr>, species <chr>, films <list>,
#> #   vehicles <list>, starships <list>

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

starwars %>% 
  mutate(name, bmi = mass / ((height / 100)  ^ 2)) %>%
  select(name:mass, bmi)
#> # A tibble: 87 x 4
#>   name           height  mass   bmi
#>   <chr>           <int> <dbl> <dbl>
#> 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
#> # ... with 82 more rows

starwars %>% 
  arrange(desc(mass))
#> # A tibble: 87 x 13
#>   name    height  mass hair_color skin_color  eye_color  birth_year gender
#>   <chr>    <int> <dbl> <chr>      <chr>       <chr>           <dbl> <chr> 
#> 1 Jabba …    175 1358. <NA>       green-tan,… orange          600.  herma…
#> 2 Grievo…    216  159. none       brown, whi… green, ye…       NA   male  
#> 3 IG-88      200  140. none       metal       red              15.0 none  
#> 4 Darth …    202  136. none       white       yellow           41.9 male  
#> 5 Tarfful    234  136. brown      brown       blue             NA   male  
#> # ... with 82 more rows, and 5 more variables: homeworld <chr>,
#> #   species <chr>, films <list>, vehicles <list>, starships <list>

starwars %>%
  group_by(species) %>%
  summarise(
    n = n(),
    mass = mean(mass, na.rm = TRUE)
  ) %>%
  filter(n > 1)
#> # A tibble: 9 x 3
#>   species      n  mass
#>   <chr>    <int> <dbl>
#> 1 Droid        5  69.8
#> 2 Gungan       3  74.0
#> 3 Human       35  82.8
#> 4 Kaminoan     2  88.0
#> 5 Mirialan     2  53.1
#> # ... with 4 more rows

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.



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dplyr documentation built on July 5, 2018, 9:04 a.m.