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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 "Lattice: Multivariate Data Visualization with R" (Final Part)}}</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}}</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
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=3-900051-07-0|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 |publisher=Springer |isbn=978-1-4419-1317-3 |doi=10.1007/978-1-4419-1318-0_16 |chapter=Graphics with ggplot2}}</ref>
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