CanvasXpress is free for personal and educational use.View Documentation →
Install the CanvasXpress Python library from PyPI and use it with Jupyter, Flask and Django.
Install the CanvasXpress Node module from npmjs to create visualizations locally or in the cloud.
Install the CanvasXpress Node modules from npmjs to easily integrate with React JS.
Install the CanvasXpress Node modules from npmjs to easily integrate with Angular JS.
Use CanvasXpress with PHP in any web environment.
Learn how these features can help you develop visualizations easily and serve your stake holders fast.
Free for individual and educational use with dual licensing. Please contact us for commercial use.See license →
Rich set of unobtrusive widgets for data analytics embedded in every visualization.Explore UI →
Visualizations optimized to enhance the user experience and facilitate data exploration.Check Software Design →
Full tracking of data, configuration and every single user interaction for Reproducible Research.Check Audit Trail →
Create visualizations starting with different file formats. Load data from JSON, XML, CSV or PNG files by simply drag and drop.Explore File Formats →
Rich and dynamic user experience to explore data with mouse-overs, zoom, clicks, resize, drag and drop, menus, tables and more.Check Interactivity →
Built-in automatic broadcast mechanism to comunicate events to all visualizations in web page to highlight, filter-in or filter-out.Explore Broadcasting →
Explore and model data sets by grouping or segregating based on meta data, sorting, clustering, transforming and much more.Check Data Wrangling →
As the size of visualizations gets larger, other packages have a steep dropoff of performance around 20k points whereas this package scales well to a million points. On-chart manipulations save network round-trips to the server/app to get chart updates.
With the wide variety of charts you can use a single library for most visualizations in your report or application.
Dynamic and reactive charts. On-chart functionality is extensive. Reproducibility, Reproducible Research
JS library updates are made frequently. CRAN package updated regularly for R. Python package is brand new in 2021!