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  2. ggplot2 - Wikipedia

    en.wikipedia.org/wiki/Ggplot2

    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 ...

  3. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.

  4. Programming with Big Data in R - Wikipedia

    en.wikipedia.org/wiki/Programming_with_Big_Data_in_R

    Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [ 2 ] [ 3 ] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical ...

  5. Category:Free R (programming language) software - Wikipedia

    en.wikipedia.org/wiki/Category:Free_R...

    The programs on this page are free software dealing with the R programming language. Free and open-source software portal Pages in category "Free R (programming language) software"

  6. Vega and Vega-Lite visualisation grammars - Wikipedia

    en.wikipedia.org/wiki/Vega_and_Vega-Lite...

    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. [3] Vega is used in the back end of several data visualization systems, for example Voyager.

  7. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Main advantage of EDA is providing the data visualization of data after conducting the analysis. Tukey's championing of EDA encouraged the development of statistical computing packages, especially S at Bell Labs. [4] The S programming language inspired the systems S-PLUS and R.

  8. Brushing and linking - Wikipedia

    en.wikipedia.org/wiki/Brushing_and_linking

    In databases, brushing and linking is the connection of two or more views of the same data, such that a change to the representation in one view affects the representation in the other. [1] Brushing and linking is also an important technique in interactive visual analysis , a method for performing visual exploration and analysis of large ...

  9. Topological data analysis - Wikipedia

    en.wikipedia.org/wiki/Topological_data_analysis

    An R package TDA is capable of calculating recently invented concepts like landscape and the kernel distance estimator. [25] The Topology ToolKit is specialized for continuous data defined on manifolds of low dimension (1, 2 or 3), as typically found in scientific visualization.