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'''ggplot2''' is a [[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 ''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|
== Updates ==
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==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]]|accessdate=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
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}}</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 |title=A Layered Grammar of Graphics |journal=Journal of Computational and Graphical Statistics |date=March 2010|volume=19|issue=1|pages=3–28|doi=10.1198/jcgs.2009.07098}}</ref>
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==Further reading==
* {{cite book|last=Wilkinson|first=Leland|
* {{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 Jun 2011|title=Engineering Data Analysis (with R and ggplot2) |url=https://www.youtube.com/watch?v=TaxJwC_MP9Q |format= |medium= |language
== External links ==
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