Bokeh is a fiscally sponsored project of NumFOCUS, a nonprofit dedicated to supporting the open-source scientific computing community. If you like Bokeh and would like to support our mission, please consider making a donation.
| Latest Release |  |
Conda |
|
| License |
|
PyPI |
|
| Sponsorship |
|
Live Tutorial |
|
| Build Status |
|
Gitter |
|
| Static Analyis |
|
|
Bokeh is an interactive visualization library for Python that 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 provides an elegant and concise way to construct versatile graphics while delivering high-performance interactivity for large or streamed datasets.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
The easiest way to install Bokeh is using the Anaconda Python distribution and its included Conda package management system. To install Bokeh and its required dependencies, enter the following command at a Bash or Windows command prompt:
conda install bokeh
To install using pip, enter the following command at a Bash or Windows command prompt:
pip install bokeh
For more information, refer to the installation documentation.
Once Bokeh is installed, check out the Getting Started section of the Quickstart guide.
Visit the Bokeh site for information and full documentation, or launch the Bokeh tutorial to learn about Bokeh in live Jupyter Notebooks.
If you would like to contribute to Bokeh, please review the Developer Guide.
Follow us on Twitter @bokehplots and on YouTube.
