CanvasXpress Python Library

About this Package

This package was recently released for general use. We maintain thorough code coverage and use the package ourselves, but it remains possible that edge use cases can be refined. We appreciate your feedback and patience.

CanvasXpress was developed as the core visualization component for bioinformatics and systems biology analysis at Bristol-Myers Squibb. It supports a large number of visualizations to display scientific and non-scientific data. CanvasXpress also includes a simple and unobtrusive user interface to explore complex data sets, a sophisticated and unique mechanism to keep track of all user customization for Reproducible Research purposes, as well as an 'out of the box' broadcasting capability to synchronize selected data points across all CanvasXpress plots in a page. Data can be easily sorted, grouped, transposed, transformed or clustered dynamically. The fully customizable mouse events as well as the zooming, panning and drag-and-drop capabilities are features that make this library unique in its class.

CanvasXpress can be now be used within Python for native integration into IPython and Web environments, such as:

Complete examples using the CanvasXpress library including the mouse events, zooming, and broadcasting capabilities are included in this package. This CanvasXpress Python package was created by Dr. Todd C. Brett, with support from Aggregate Genius Inc., in cooperation with the CanvasXpress team.

The maintainer of the Python edition of this package is Dr. Todd C. Brett.

Getting Started

This documentation site contains working examples and API documentation. Be sure to read these resources, as well as the wealth of additional information, including full Javascript API documentation, at https://www.canvasxpress.org.

Why not begin by jumping right on in?!