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Interactive Web Plotting for Python

Home Page: http://bokeh.pydata.org/en/latest/

License: BSD 3-Clause "New" or "Revised" License

Python 58.23% JavaScript 1.43% HTML 1.28% TypeScript 5.23% CoffeeScript 30.35% CSS 3.08% Batchfile 0.04% Shell 0.21% Makefile 0.03% Jupyter Notebook 0.11%

bokeh's Introduction

Bokeh

Latest Release latest release
License Bokeh license
Build Status build status
Conda conda downloads
PyPI
Gitter
Twitter

Bokeh, a Python interactive visualization library, enables beautiful and meaningful visual presentation of data in modern web browsers. With Bokeh, you can quickly and easily create interactive plots, dashboards, and data applications.

Bokeh helps provide elegant, concise construction of novel graphics in the style of D3.js, while also delivering high-performance interactivity over very large or streaming datasets.

Interactive gallery

image anscombe stocks lorenz candlestick scatter splom
iris histogram periodic choropleth burtin streamline image_rgba
stacked quiver elements boxplot categorical unemployment les_mis

Installation

We recommend using the Anaconda Python distribution and conda to install Bokeh. Enter this command at a Bash or Windows command prompt:

conda install bokeh

This installs Bokeh and all needed dependencies.

To begin using Bokeh or to install using pip, follow the Quickstart documentation.

Documentation

Visit the Bokeh web page for information and full documentation.

Contribute to Bokeh

To contribute to Bokeh, please review the Developer Guide.

Follow us

Follow us on Twitter @bokehplots and on YouTube.

bokeh's People

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