Software:Ggplot2: Difference between revisions

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{{Short description|Data visualization package for R}}
{{Infobox software
{{Infobox software
| name = ggplot2
| name = ggplot2
| title = ggplot2
| title = ggplot2
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| logo = Ggplot2 hex logo.svg
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   | footer    = ggplot2 and base graphics defaults for a simple scatterplot image
   | footer    = ggplot2 and base graphics defaults for a simple scatterplot image
   | image1    = Ggplot2scatter.png
   | image1    = Ggplot2 scatter plot.svg
   | alt1      = ggplot2
   | alt1      = ggplot2
   | caption1  = ggplot2
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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 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, ggplot 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 21 December 2015, ggplot2 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>
 
On 11 September 2025, ggplot2 4.0.0 was released. The accompanying blog post indicated that the release included "a rewrite of the object oriented system from S3 to S7, large new features to smaller quality of life improvements and bugfixes."<ref>{{cite web |url=https://www.tidyverse.org/blog/2025/09/ggplot2-4-0-0/ |access-date=2025-09-11 |title=ggplot 4.0.0 |date=11 September 2025 }}</ref>


==Comparison with base graphics and other packages==
==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=[[Company:Revolution Analytics|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>
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=[[Company:Revolution Analytics|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 a different plot for various subsets of the data 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>
Creating separate plots for various subsets of data in base R requires loops and manual management, 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>
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.|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>
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=[[Organization:R Foundation for Statistical Computing|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.|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==
==Related projects==
* ggplot for Python,<ref>{{cite web |title=yhat/ggpy: ggplot port for python |url=https://github.com/yhat/ggpy |access-date=2024-02-01 |website=[[GitHub]] |publisher=yhat}}</ref> but has not been updated since 2016-11-20
See implementations of The Grammar of Graphics.
* plotnine<ref>{{cite web |url=https://plotnine.readthedocs.io/en/stable/about-plotnine.html |title=plotnine |access-date=2 August 2023}}</ref> started as an effort to improve the scalability of ggplot for Python and is largely compatible with ggplot2 syntax.
* 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|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 ==
== References ==
Line 73: Line 71:
==Further reading==
==Further reading==
* {{cite book|last=Wilkinson|first=Leland|title=The Grammar of Graphics|year=2005|publisher=Springer|isbn=978-0-387-98774-3}}
* {{cite book|last=Wilkinson|first=Leland|title=The Grammar of Graphics|year=2005|publisher=Springer|isbn=978-0-387-98774-3}}
* {{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=[[Company:Springer Science+Business Media|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}}
* {{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}}


== External links ==
== External links ==
* {{Official website|https://ggplot2.tidyverse.org/}}
* {{GitHub|tidyverse/ggplot2}}
* {{GitHub|tidyverse/ggplot2}}


{{R (programming language)}}
{{Statistical software}}
{{Statistical software}}


[[Category:Cross-platform free software]]
[[Category:Cross-platform free software]]
[[Category:Free data visualization software]]
[[Category:Free plotting software]]
[[Category:Free plotting software]]
[[Category:Free R (programming language) software]]
[[Category:Free R (programming language) software]]
[[Category:Free data analysis software]]
[[Category:Visualization API]]


{{Sourceattribution|Ggplot2}}
{{Sourceattribution|Ggplot2}}

Latest revision as of 05:16, 11 April 2026

ggplot2
Original author(s)Hadley Wickham, Winston Chang
Initial release10 June 2007; 18 years ago (2007-06-10)
Written inR
LicenseMIT license
Websiteggplot2.tidyverse.org

ggplot2
ggplot2
Base graphics
Base graphics
ggplot2 and base graphics defaults for a simple scatterplot image

ggplot2 is an open-source data visualization package for the statistical 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.[1][2][3]

Updates

On 2 March 2012, ggplot2 version 0.9.0 was released with numerous changes to internal organization, scale construction and layers.[4]

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".[5]

On 21 December 2015, ggplot2 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."[6]

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.[7][8]

On 11 September 2025, ggplot2 4.0.0 was released. The accompanying blog post indicated that the release included "a rewrite of the object oriented system from S3 to S7, large new features to smaller quality of life improvements and bugfixes."[9]

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.[10] This abstraction comes at a cost, with ggplot2 being slower than lattice graphics.[11]

Creating separate plots for various subsets of data in base R requires loops and manual management, whereas ggplot2 simplifies that process with a collection of "facet" functions to choose from.[12]

One potential limitation of base R graphics is the "pen-and-paper model" utilized to populate the plotting device.[13] Graphical output from the interpreter is added directly to the plotting device or window, rather than separately for each distinct element of a plot.[14] In this respect it is similar to the lattice package, though Wickham argues ggplot2 inherits a more formal model of graphics from Wilkinson.[15] As such, it allows for a high degree of modularity; the same underlying data can be transformed by many different scales or layers.[16][17]

Plots may be created via the convenience function qplot() where arguments and defaults are meant to be similar to base R's plot() function.[18][19] More complex plotting capacity is available via ggplot() which exposes the user to more explicit elements of the grammar.[20]

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.[21] 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.[21]

See implementations of The Grammar of Graphics.

References

  1. ↑ Wickham, Hadley (July 2010). "ggplot2: Elegant Graphics for Data Analysis". Journal of Statistical Software 35 (1). http://www.jstatsoft.org/v35/b01/paper. 
  2. ↑ Wilkinson, Leland (June 2011). "ggplot2: Elegant Graphics for Data Analysis by WICKHAM, H". Biometrics 67 (2): 678–679. doi:10.1111/j.1541-0420.2011.01616.x. 
  3. ↑ "CRAN - Package ggplot2". 12 October 2023. https://cran.r-project.org/web/packages/ggplot2/index.html. 
  4. ↑ ggplot2 Development Team. "Changes and Additions to ggplot2-0.9.0". https://cloud.github.com/downloads/hadley/ggplot2/guide-col.pdf. 
  5. ↑ Wickham, Hadley. "ggplot2 development". ggplot2 Google Group. https://groups.google.com/d/msg/ggplot2/SSxt8B8QLfo/J2dfKR92rsYJ. 
  6. ↑ "ggplot 2.0.0". 21 December 2015. https://blog.rstudio.com/2015/12/21/ggplot2-2-0-0/. 
  7. ↑ "ggplot2 3.0.0" (in en-us). https://www.tidyverse.org/blog/2018/07/ggplot2-3-0-0/. 
  8. ↑ Wickham, Hadley (in en). 19 Quasiquotation | Advanced R. https://adv-r.hadley.nz/quasiquotation.html. 
  9. ↑ "ggplot 4.0.0". 11 September 2025. https://www.tidyverse.org/blog/2025/09/ggplot2-4-0-0/. 
  10. ↑ Smith, David. "Create beautiful statistical graphics with ggplot2". Revolutions. Revolution Analytics. http://blog.revolutionanalytics.com/2009/01/create-beautiful-statistical-graphics-with-ggplot2.html. 
  11. ↑ "ggplot2 Version of Figures in "Lattice: Multivariate Data Visualization with R" (Final Part)". 25 August 2009. http://learnr.wordpress.com/2009/08/26/ggplot2-version-of-figures-in-lattice-multivariate-data-visualization-with-r-final-part/. 
  12. ↑ Yau, Nathan (22 March 2016). "Comparing ggplot2 and R Base Graphics" (in en). https://flowingdata.com/2016/03/22/comparing-ggplot2-and-r-base-graphics/. 
  13. ↑ Wickham, Hadley (2009). ggplot2: Elegant Graphics for Data Analysis. Springer. pp. 5. ISBN 978-0-387-98140-6. 
  14. ↑ Murrell, Paul (August 2009). "R Graphics". Wiley Interdisciplinary Reviews: Computational Statistics 1 (2): 216–220. doi:10.1002/wics.22. 
  15. ↑ Sarkar, Deepayan (2008). Lattice: multivariate data visualization with R. Springer. pp. xi. ISBN 978-0-387-75968-5. 
  16. ↑ Teetor, Paul (2011). R Cookbook. O'Reilly. pp. 223. ISBN 978-0-596-80915-7. 
  17. ↑ Wickham, Hadley (March 2010). "A Layered Grammar of Graphics". Journal of Computational and Graphical Statistics 19 (1): 3–28. doi:10.1198/jcgs.2009.07098. http://vita.had.co.nz/papers/layered-grammar.pdf. 
  18. ↑ R Development Core Team (2011). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. ISBN 978-3-900051-07-5. http://www.R-project.org/. 
  19. ↑ Ginestet, Cedric (January 2011). "ggplot2: Elegant Graphics for Data Analysis". Journal of the Royal Statistical Society, Series A 174 (1): 245–246. doi:10.1111/j.1467-985X.2010.00676_9.x. 
  20. ↑ Muenchen, Robert A.; Hilbe, Joseph M (2010). "Graphics with ggplot2". R for Stata Users. Statistics and Computing. Springer. pp. 385–452. doi:10.1007/978-1-4419-1318-0_16. ISBN 978-1-4419-1317-3. 
  21. ↑ 21.0 21.1 Kopf, Dan (2017-06-18). "All hail ggplot2—The code powering all those excellent charts is 10 years old" (in en). https://qz.com/1007328/all-hail-ggplot2-the-code-powering-all-those-excellent-charts-is-10-years-old. 

Further reading

  • Wilkinson, Leland (2005). The Grammar of Graphics. Springer. ISBN 978-0-387-98774-3. 
  • Wickham, Hadley (6 June 2011). Engineering Data Analysis (with R and ggplot2). Google Tech Talks.
  • Wickham, Hadley (2016). ggplot2: Elegant Graphics for Data Analysis (2nd ed.). Springer Science+Business Media. ISBN 978-3319242750. https://ggplot2-book.org/. 
  • Wickham, Hadley (2017). R for Data Science. O'Reilly Media. ISBN 978-1491910399. https://r4ds.had.co.nz/. 

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