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Free and open-source software portal; This is a category of articles relating to data visualization software which can be freely used, copied, studied, modified, and redistributed by everyone that obtains a copy: "free software" or "open source software".
A visual programming data-flow software suite with widgets for statistical data analysis, interactive data visualization, data mining, and machine learning. Origin: GUI, COM, C/ C++ and scripting: proprietary: No 1992: June 22, 2017 / 2017 SR2: Windows: Multi-layer 2D, 3D and statistical graphs for science and engineering. Built-in digitizing tool.
RAWGraphs is a web-based open-source data visualization software made in JavaScript. It employs D3.js for the creation of editable visualizations in SVG format. History
Tools. Tools. move to sidebar hide. ... Free data visualization software (21 P) G. ... Pages in category "Data visualization software"
QtiPlot is a data analysis and scientific visualisation program, similar to Origin. ROOT is a free object-oriented multi-purpose data-analysis package, developed at CERN. Salome is a free software tool that provides a generic platform for pre- and post-processing for numerical simulation.
Plotly is a technical computing company headquartered in Montreal, Quebec, that develops online data analytics and visualization tools. Plotly provides online graphing, analytics, and statistics tools for individuals and collaboration, as well as scientific graphing libraries for Python, R, MATLAB, Perl, Julia, Arduino, JavaScript [1] and REST.
This is a list of free and open-source software packages , computer software licensed under free software licenses and open-source licenses. Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]
VisIt is an open-source application for large-scale simulated and experimental data sets. The application serves as an infrastructure for parallelized, general post-processing of extremely massive data sets. Its primary use cases include data exploration, comparative analysis, visual debugging, quantitative analysis, and presentation.