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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.
Example of a bagplot created in R. A bagplot, or starburst plot, [1] [2] is a method in robust statistics for visualizing two-or three-dimensional statistical data, analogous to the one-dimensional box plot. Introduced in 1999 by Rousseuw et al., the bagplot allows one to visualize the location, spread, skewness, and outliers of a data set. [3]
Interactive Data Visualization using Mondrian, in Journal of Statistical Software 7 (11): 1–9. Theus, M. and Urbanek, S. (2008). Interactive Graphics for Data Analysis: Principles and Examples (Computer Science and Data Analysis), Chapman & Hall / CRC.
IGOR Pro, a software package with emphasis on time series, image analysis, and curve fitting. It comes with its own programming language and can be used interactively. LabPlot is a data analysis and visualization application built on the KDE Platform. MFEM is a free, lightweight, scalable C++ library for finite element methods.
The R package Rtsne implements t-SNE in R. ELKI contains tSNE, also with Barnes-Hut approximation; scikit-learn, a popular machine learning library in Python implements t-SNE with both exact solutions and the Barnes-Hut approximation. Tensorboard, the visualization kit associated with TensorFlow, also implements t-SNE (online version)
Example and code for the R statistical software environment; Example and code for Python using the matplotlib library; ChernoffFace package in Python using the matplotlib library; Function ChernoffFace in Wolfram Language (Mathematica) at Wolfram Function Repository; Example code for MATLAB using Statistics and Machine Learning Toolbox.
The software's primary applications are for designed experiments and analyzing statistical data from industrial processes. [7] JMP can be used in conjunction with the R and Python open source programming languages to access features not available in JMP itself. [42] JMP software is partly focused on exploratory data analysis and visualization.
Interactive data visualization enables direct actions on a graphical plot to change elements and link between multiple plots. [56] Interactive data visualization has been a pursuit of statisticians since the late 1960s. Examples of the developments can be found on the American Statistical Association video lending library. [57] Common ...