Ggplot2: Difference between revisions

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'''ggplot2''' is an [[open-source]] [[data visualization]] [[R package|package]] for the [[Computational statistics|statistical programming]] language [[R (programming language)|R]]. Created by [[Hadley Wickham]] in 2005, ggplot2 is an implementation of [[Leland Wilkinson]]'s ''[[Wilkinson's Grammar of Graphics|Grammar of Graphics]]''—a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers. ggplot2 can serve as a replacement for the base graphics in R and contains a number of defaults for web and print display of common scales. Since 2005, ggplot2 has grown in use to become one of the most popular R packages.<ref>{{cite journal|last=Wickham|first=Hadley|title=ggplot2: Elegant Graphics for Data Analysis|journal=Journal of Statistical Software|date=July 2010|volume=35|issue=1|url=http://www.jstatsoft.org/v35/b01/paper}}</ref><ref>{{cite journal|last=Wilkinson|first=Leland|author-link=Leland Wilkinson|title=ggplot2: Elegant Graphics for Data Analysis by WICKHAM, H|journal=Biometrics|date=June 2011|volume=67|issue=2|pages=678–679|doi=10.1111/j.1541-0420.2011.01616.x}}</ref><ref>{{cite web|url=https://cran.r-project.org/web/packages/ggplot2/index.html|title=CRAN - Package ggplot2|date=12 October 2023 }}</ref>

== Updates ==

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On 25 February 2014, Hadley Wickham formally announced that "ggplot2 is shifting to maintenance mode. This means that we are no longer adding new features, but we will continue to fix major bugs, and consider new features submitted as pull requests. In recognition [of] this significant milestone, the next version of ggplot2 will be 1.0.0".<ref>{{cite web |last=Wickham|first=Hadley|title=ggplot2 development|url= https://groups.google.com/d/msg/ggplot2/SSxt8B8QLfo/J2dfKR92rsYJ|publisher=ggplot2 Google Group|access-date=26 February 2014}}</ref>

On 21 December 2015, ggplotggplot2 2.0.0 was released. In the announcement, it was stated that "ggplot2 now has an official extension mechanism. This means that others can now easily create their [own] stats, geoms and positions, and provide them in other packages."<ref>{{cite web |url=https://blog.rstudio.com/2015/12/21/ggplot2-2-0-0/ |access-date=2021-06-21 |title=ggplot 2.0.0 |date=21 December 2015 |archive-url=https://web.archive.org/web/20210207054047/https://blog.rstudio.com/2015/12/21/ggplot2-2-0-0/ |archive-date=2021-02-07 |url-status=live}}</ref>

On 5 July 2018, ggplot2 3.0.0 was released (initially planned as a ggplot2 2.3.0). This now provides support for tidy evaluation allowing quasiquotation in ggplot2 functions.<ref>{{Cite web |title=ggplot2 3.0.0 |url=https://www.tidyverse.org/blog/2018/07/ggplot2-3-0-0/ |access-date=2025-07-13 |website=www.tidyverse.org |language=en-us}}</ref><ref>{{Cite book |last=Wickham |first=Hadley |url=https://adv-r.hadley.nz/quasiquotation.html |title=19 Quasiquotation {{!}} Advanced R |language=en}}</ref>

==Comparison with base graphics and other packages==

In contrast to base R graphics, ggplot2 allows the user to add, remove or alter components in a plot at a high level of abstraction.<ref>{{cite web|last=Smith|first=David|title=Create beautiful statistical graphics with ggplot2|url=http://blog.revolutionanalytics.com/2009/01/create-beautiful-statistical-graphics-with-ggplot2.html|work=Revolutions|publisher=[[Revolution Analytics]]|access-date=11 July 2011}}</ref> This abstraction comes at a cost, with ggplot2 being slower than lattice graphics.<ref>{{cite web|url=http://learnr.wordpress.com/2009/08/26/ggplot2-version-of-figures-in-lattice-multivariate-data-visualization-with-r-final-part/|title=ggplot2 Version of Figures in "Lattice: Multivariate Data Visualization with R" (Final Part)|date=25 August 2009 }}</ref>

Creating aseparate different plotplots for various subsets of the data in base R requires for loops and manual management in base R graphics, whereas ggplot2 simplifies that process with a collection of "facet" functions to choose from.<ref>{{cite web |last1=Yau |first1=Nathan |title=Comparing ggplot2 and R Base Graphics |url=https://flowingdata.com/2016/03/22/comparing-ggplot2-and-r-base-graphics/ |website=FlowingData |access-date=17 April 2022 |language=en |date=22 March 2016}}</ref>

One potential limitation of base R graphics is the "pen-and-paper model" utilized to populate the plotting device.<ref>{{cite book|last=Wickham|first=Hadley|title=ggplot2: Elegant Graphics for Data Analysis |year=2009 |publisher=Springer |isbn=978-0-387-98140-6|pages=5}}</ref> Graphical output from the interpreter is added directly to the plotting device or window, rather than separately for each distinct element of a plot.<ref>{{cite journal |last=Murrell |first=Paul |title=R Graphics|journal=Wiley Interdisciplinary Reviews: Computational Statistics|date=August 2009|volume=1|issue=2|pages=216–220|doi=10.1002/wics.22|s2cid=37743308 }}</ref> In this respect it is similar to the lattice package, though Wickham argues ggplot2 inherits a more formal model of graphics from Wilkinson.<ref>{{cite book|last=Sarkar|first=Deepayan|title=Lattice: multivariate data visualization with R|year=2008|publisher=Springer|isbn=978-0-387-75968-5|pages=xi}}</ref> As such, it allows for a high degree of modularity; the same underlying data can be transformed by many different scales or layers.<ref>{{cite book|last=Teetor|first=Paul|title=R Cookbook|year=2011|publisher=O'Reilly|isbn=978-0-596-80915-7|pages=223}}</ref><ref>{{cite journal|last=Wickham|first=Hadley|date=March 2010|title=A Layered Grammar of Graphics|url=http://vita.had.co.nz/papers/layered-grammar.pdf|journal=Journal of Computational and Graphical Statistics|volume=19|issue=1|pages=3–28|doi=10.1198/jcgs.2009.07098|s2cid=58971746}}</ref>

Plots may be created via the convenience function <code>qplot()</code> where arguments and defaults are meant to be similar to base R's <code>plot()</code> function.<ref>{{cite book|title=R: A language and environment for statistical computing|year=2011|publisher=R Foundation for Statistical Computing|___location=Vienna, Austria|isbn=978-3-900051-07-5|url=http://www.R-project.org/|author=R Development Core Team}}</ref><ref>{{cite journal|last=Ginestet|first=Cedric|title=ggplot2: Elegant Graphics for Data Analysis |journal=Journal of the Royal Statistical Society, Series A |date=January 2011 |volume=174 |issue=1 |pages=245–246 |doi=10.1111/j.1467-985X.2010.00676_9.x}}</ref> More complex plotting capacity is available via <code>ggplot()</code> which exposes the user to more explicit elements of the grammar.<ref>{{cite book|last1=Muenchen|first1=Robert A.|title=R for STATA Users|last2=Hilbe|first2=Joseph M |title=R for Stata Users |publisher=Springer |isbn=978-1-4419-1317-3 |doi=10.1007/978-1-4419-1318-0_16 |chapter=Graphics with ggplot2|series=Statistics and Computing|year=2010|pages=385–452}}</ref>

== Impact ==

After ten years of being developed, ggplot2 has continued to make an impact on the data visualization community: it has had over 10 million downloads, up to 400,000 downloads in a given month, and is used by data scientists from the US government to journalists at ''[[The New York Times]]'' to analyze and present data.<ref name=":0">{{Cite web |last=Kopf |first=Dan |date=2017-06-18 |title=All hail ggplot2—The code powering all those excellent charts is 10 years old |url=https://qz.com/1007328/all-hail-ggplot2-the-code-powering-all-those-excellent-charts-is-10-years-old |access-date=2025-05-13 |website=Quartz |language=en}}</ref> Wickham posits the success of ggplot2 comes from the increased popularity of the R language and the relative ease of making aesthetically appealing graphics. Along with more serious uses of ggplot2, Wickham also supports the more unusual use cases, like exploring factors for winning in the reality TV show [[RuPaul's Drag Race]].<ref name=":0" />

==Related projects==

See [[Wilkinson's Grammar of Graphics#Related projects|implementations of The Grammar of Graphics]].

* ggplot for Python<ref>{{cite web |url=https://github.com/yhat/ggplot/ |title=ggplot for Python |publisher=yhat |access-date=12 October 2014}}</ref>

* Plotly - Interactive, online ggplot2 graphs<ref>{{cite web |url=https://plot.ly/ggplot2/ |title=Interactive, online ggplot2 graphs |publisher=plotly |access-date=12 October 2014}}</ref>

* gramm, a plotting class for MATLAB inspired by ggplot2<ref>{{cite web|title=ggplot for Matlab|url=https://github.com/piermorel/gramm|publisher=gramm|access-date=11 December 2015}}</ref>

* gadfly, a system for plotting and visualization written in [[Julia (programming language)|Julia]], based largely on ggplot2<ref>{{cite web|title=Gadfly.jl|url=http://gadflyjl.org|access-date=11 September 2018}}</ref>

* Chart::GGPlot - ggplot2 port in [[Perl]]<ref>{{cite web|title= Stephan Loyd/Chart-GGPlot-0.0001|url=https://metacpan.org/release/Chart-GGPlot|access-date=30 March 2019}}</ref>

* The Lets-Plot for Python library includes a native backend and a Python API, which was mostly based on the ggplot2 package well-known to data scientists who use R.<ref>{{cite web |url=https://github.com/JetBrains/lets-plot |title=JetBrains/lets-plot |publisher=JetBrains |access-date=3 April 2021}}</ref>

* Lets-Plot is an open-source plotting library for statistical data. It is implemented using the Kotlin programming language and is built on the principles of layered graphics first described in the Leland Wilkinson work The Grammar of Graphics.<ref>{{cite web|title=JetBrains/lets-plot-kotlin|url=https://github.com/JetBrains/lets-plot-kotlin|url-status=live|access-date=4 April 2021|publisher=JetBrains}}</ref>

* ggplotnim, plotting library using the [[Nim (programming language)|Nim]] programming language inspired by ggplot2.<ref>{{cite web |url=https://github.com/Vindaar/ggplotnim |title=ggplotnim |publisher=Vindaar |access-date=1 August 2023}}</ref>

== References ==

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==Further reading==

* {{cite book|last=Wilkinson|first=Leland|author-link=Leland Wilkinson|title=The Grammar of Graphics|year=2005|publisher=Springer|isbn=978-0-387-98774-3}}

* {{cite book|last=Wickham|first=Hadley|title=R for Data Science|url=https://r4ds.had.co.nz/|year=2017|publisher=O'Reilly Media|isbn=978-1491910399}}

* {{cite video |people= Wickham, Hadley|date= 6 June 2011|title=Engineering Data Analysis (with R and ggplot2) |url=https://www.youtube.com/watch?v=TaxJwC_MP9Q |publisher= Google Tech Talks}}

* {{cite book|last=Wickham|first=Hadley|title=ggplot2: Elegant Graphics for Data Analysis|url=https://ggplot2-book.org/|year=2016|publisher=[[Springer Science+Business Media]]|isbn=978-3319242750|edition=2nd}}

* {{cite book|last=Wickham|first=Hadley|title=R for Data Science|url=https://r4ds.had.co.nz/|year=2017|publisher=O'Reilly Media|isbn=978-1491910399}}

== External links ==

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[[Category:Cross-platform free software]]

[[Category:Free data and information visualization software]]

[[Category:Free plotting software]]

[[Category:Free R (programming language) software]]

[[Category:Free data analysis software]]

[[Category:Visualization API]]

[[Category:Software using the MIT license]]