Civil Rights
Movements, leaders, victories and the continuing fight for equality.
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Movements, leaders, victories and the continuing fight for equality.
Innovation, patents, science, technology and world-changing contributions.
Pioneers, champions, Negro Leagues, records, activism and excellence.
Meet the people whose lives, choices and achievements shaped the journey.
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Moments that changed communities, movements, institutions and the nation.
Wilmington, North Carolina once had a thriving Black middle class and an elected interracial government. In 1898 white supremacists used violence to overthrow that government, kill Black residents and drive many others from the city.
MORE →Reflects the personal views, recollections, and perspective of the author, Mike Davis.
This is a personal recollection on the Move fire on May 13, 1985
| ggplot2 | |
|---|---|
 | |
| Original authors | Hadley Wickham, Winston Chang |
| Release | 10 June 2007 |
| Stable release | 4.0.3[1]
/ 22 April 2026 |
| Written in | R |
| License | MIT license |
| Website | ggplot2 |
| Repository | |
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.[2][3][4]
On 2 March 2012, ggplot2 version 0.9.0 was released with numerous changes to internal organization, scale construction and layers.[5]
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".[6]
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."[7]
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.[8][9]
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."[10]
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.[11] This abstraction comes at a cost, with ggplot2 being slower than lattice graphics.[12]
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.[13]
One potential limitation of base R graphics is the "pen-and-paper model" utilized to populate the plotting device.[14] Graphical output from the interpreter is added directly to the plotting device or window, rather than separately for each distinct element of a plot.[15] In this respect it is similar to the lattice package, though Wickham argues ggplot2 inherits a more formal model of graphics from Wilkinson.[16] As such, it allows for a high degree of modularity; the same underlying data can be transformed by many different scales or layers.[17][18]
Plots may be created via the convenience function qplot() where arguments and defaults are meant to be similar to base R's plot() function.[19][20] More complex plotting capacity is available via ggplot() which exposes the user to more explicit elements of the grammar.[21]
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.[22] 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.[22]
See implementations of The Grammar of Graphics.
{{cite web}}: CS1 maint: numeric names: authors list (link)
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Source: Wikipedia. Article content is retrieved live through the MediaWiki API.
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.
Hadley Alexander Wickham (born 14 October 1979) is a New Zealand statistician known for his work on open-source software for the R statistical programming environment. He is the chief scientist at Posit PBC and an adjunct professor of statistics at the University of Auckland, Stanford University, and Rice University. His work includes the data visualisation system ggplot2 and the tidyverse, a collection of R packages for data science based on the concept of tidy data.
A mosaic plot, Marimekko chart, Mekko chart, or sometimes percent stacked bar plot, is a graphical visualization of data from two or more qualitative variables. It is the multidimensional extension of spineplots, which graphically display the same information for only one variable. Although the term spineplot was originally used by Hummel to describe univariate graphs, Cox points out that the term has also been broadly applied to displays of two or more variables. The mosaic plot makes it possible to visualise relationships between different categorical variables. For example, independence is shown when the boxes across categories all have the same areas. Mosaic plots were introduced by Hartigan and Kleiner in 1981 and expanded on by Friendly in 1994. Mosaic plots are also called Marimekko or Mekko charts because they resemble some Marimekko prints. As with bar charts and spineplots, the area of the tiles, also known as the bin size, is proportional to the number of observations within that category. Although mosaic plots most commonly show the relative frequency of each combination of values, they can also be used to display the goodness with which a loglinear model fits the data.[1] Mosaic plot construction is described and illustrated in detailed worked example by Jeppson and Hoffman using the ggplot2 package in the R language.
Vega and Vega-Lite are visualization tools implementing a grammar of graphics, similar to ggplot2. The Vega and Vega-Lite grammars extend Leland Wilkinson's Grammar of Graphics by adding a novel grammar of interactivity to assist in the exploration of complex datasets. Vega acts as a low-level language suited to explanatory figures (the same use case as D3.js), while Vega-Lite is a higher-level language suited to rapidly exploring data. Vega is used in the backend of several data visualization systems, for example Voyager. Chart specifications are written in JSON and rendered in a browser or exported to either vector or bitmap images. Bindings for Vega-Lite have been written in several programming languages, such as the Python package Altair. The grammars and associated tools are open source projects led by the University of Washington Interactive Data Lab and released under a BSD-3 license.
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
MORE →Shirley Chisholm, elected in 1968.