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CanvasXpress is free for personal and educational use.

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NPM
Yarn
CDN

$ yarn add canvasxpress

<link rel="stylesheet" href="http://181wej.wcbzw.com/dist/canvasXpress.css"type="text/css"/>
 <script type="text/javascript"src="http://181wej.wcbzw.com/dist/canvasXpress.min.js"></script>

茄子加速器打不开了-雷霆加器速

R Integration

Install the CanvasXpress R package from CRAN and use it in the R console, R-Studio or in any Shiny application.

Node Integration

Install the CanvasXpress Node modules from npmjs to programmatically create visualization in the command line locally or in the cloud.

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Install the CanvasXpress Node modules from npmjs to easily integrate with React JS. Examples included.

Angular Integration

Install the CanvasXpress Node modules from npmjs to easily integrate with Angular JS. Examples included.

Explore all features

Documentation Examples API References

Getting Started

Overview Installation User Interface Audit Trail

Core Concepts

Constructor Arguments DOM Data Configuration Events Instances green加速器下载

茄子加速器打不开了-雷霆加器速

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.

茄子加速器打不开了-雷霆加器速

Learn how these features can help you develop visualizations easily and serve your stake holders fast.

Open Source

Free for non-commercial and academic use. Please contact us for commercial use. Software released as GPL3.

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User Interface

Rich set of unobtrusive widgets for data analytics embedded in every visualization.

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Software Design

Visualizations optimized to enhance the user experience and facilitate data exploration.

Audit Trail

Full tracking of data, configuration and every single user interaction for Reproducible Research.

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File Formats

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Rich and dynamic user experience to explore data with mouse-overs, zoom, clicks, resize, drag and drop, menus, tables and more.

Broadcast Events

Built-in automatic broadcast mechanism to comunicate events to all visualizations in web page to highlight, filter-in or filter-out.

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Explore and model data sets by grouping or segregating based on meta data, sorting, clustering, transforming and much more.

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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!