CanvasXpress: A JavaScript Library for Data Analytics with Full Audit Trail Capabilities.
Get License Explore ExamplesCanvasXpress is free for personal and educational use.
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Install the CanvasXpress R package from CRAN and use it in the R console, R-Studio or in any Shiny application.
Install the CanvasXpress Node modules from npmjs to programmatically create visualization in the command line locally or in the cloud.
Install the CanvasXpress Node modules from npmjs to easily integrate with React JS. Examples included.
Install the CanvasXpress Node modules from npmjs to easily integrate with Angular JS. Examples included.
CanvasXpress a stand-alone JavaScript Library for Data Analytics. Built for the purpose of reproducible research with a sophisticated and unobtrusive user interface. Full and effortless audit trail of data, configuration and all user interactions in every visualization.
Learn how these features can help you develop visualizations easily and serve your stake holders fast.
Free for non-commercial and academic use. Please contact us for commercial use. Software released as GPL3.
Learn MoreRich set of unobtrusive widgets for data analytics embedded in every visualization.
Learn MoreVisualizations optimized to enhance the user experience and facilitate data exploration.
Full tracking of data, configuration and every single user interaction for Reproducible Research.
Learn MoreCreate visualizations starting with different file formats. Load data from JSON, XML, CSV or PNG files by simply drag and drop.
Learn MoreRich and dynamic user experience to explore data with mouse-overs, zoom, clicks, resize, drag and drop, menus, tables and more.
Built-in automatic broadcast mechanism to comunicate events to all visualizations in web page to highlight, filter-in or filter-out.
Learn MoreExplore and model data sets by grouping or segregating based on meta data, sorting, clustering, transforming and much more.
You want to show your data and let your audience explore it. You want to keep track of what they did during the data exploration. You want to do all this fast!
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