Interactive Web Plotting with Bokeh in IPython notebook
Clone or download
Latest commit 49fe8c2 Oct 22, 2018
Type Name Latest commit message Commit time
Failed to load latest commit information.
images update all notebooks Aug 29, 2017
quickstart Fix typo (#62) Oct 22, 2018
tutorial update bokeh app notebook Aug 16, 2018
.gitignore Update intro with bubble example Jun 13, 2015
LICENSE.txt Create LICENSE.txt Jul 27, 2017 Update Dec 16, 2017
environment.yml Make Tutorial notebooks run with binder (#61) Jul 20, 2018
index.ipynb update index Aug 16, 2018
postBuild Make Tutorial notebooks run with binder (#61) Jul 20, 2018

Bokeh in Jupyter Notebooks

Welcome to Bokeh in Jupyter Notebooks!

Bokeh is a Python interactive visualization library for large datasets that natively uses the latest web technologies. Its goal is to provide elegant, concise construction of novel graphics in the style of Protovis/D3, while delivering high-performance interactivity over large data to thin clients.

These Jupyter notebooks provide useful Bokeh examples and a tutorial to get started. You can visualize the rendered Jupyter notebooks on NBViewer or download the repository and execute jupyter notebook from your terminal.

You can also immediately launch live versions of the Tutorial notebooks in your browser on mybinder.

Please visit the Bokeh web page for more information and full documentation.

Be sure to follow us on Twitter @BokehPlots!