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https://github.com/bokeh/bokeh

Interactive Data Visualization in the browser, from Python
https://github.com/bokeh/bokeh

bokeh data-visualisation interactive-plots javascript jupyter notebooks numfocus plots plotting python visualisation visualization

Last synced: 7 months ago
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Interactive Data Visualization in the browser, from Python

Awesome Lists containing this project

README 

          

  

  Bokeh logo -- text is white in dark theme and black in light theme



----



[Bokeh](https://bokeh.org) is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics and affords high-performance interactivity across large or streaming datasets. Bokeh can help anyone who wants to create interactive plots, dashboards, and data applications quickly and easily.



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    Bokeh-tagged questions on Stack Overflow

     

  



*Consider [making a donation](https://opencollective.com/bokeh) if you enjoy using Bokeh and want to support its development.*



![4x9 image grid of Bokeh plots](https://user-images.githubusercontent.com/1078448/190840954-dc243c99-9295-44de-88e9-fafd0f4f7f8a.jpg)



## Installation



To install Bokeh and its required dependencies using `pip`, enter the following command at a Bash or Windows command prompt:

```

pip install bokeh

```



To install using `conda`, enter the following command at a Bash or Windows command prompt:



```

conda install bokeh

```



Refer to the [installation documentation](https://docs.bokeh.org/en/latest/docs/first_steps/installation.html) for more details.



## Resources



Once Bokeh is installed, check out the [first steps guides](https://docs.bokeh.org/en/latest/docs/first_steps.html#first-steps-guides).



Visit the [full documentation site](https://docs.bokeh.org) to view the [User's Guide](https://docs.bokeh.org/en/latest/docs/user_guide.html) or [checkout the Bokeh tutorial repository](https://github.com/bokeh/tutorial/) to learn about Bokeh in live Jupyter Notebooks.



Community support is available on the [Project Discourse](https://discourse.bokeh.org).



If you would like to contribute to Bokeh, please review the [Contributor Guide](https://docs.bokeh.org/en/latest/docs/dev_guide.html) and [request an invitation to the Bokeh Dev Slack workspace](https://slack-invite.bokeh.org/).



*Note: Everyone who engages in the Bokeh project's discussion forums, codebases, and issue trackers is expected to follow the [Code of Conduct](https://github.com/bokeh/bokeh/blob/HEAD/docs/CODE_OF_CONDUCT.md).*



## Support



### Fiscal Support



The Bokeh project is grateful for [individual contributions](https://opencollective.com/bokeh), as well as for present and past monetary support from the organizations and companies listed below:



  

    

    NumFocus Logo

    

  



  

    

    CZI Logo

    

  



  

    

    Blackstone Logo

    

  



 

 



  

    

    TideLift Logo

    

  



  

    

    Anaconda Logo

    

  



  

    

    NVidia Logo

    

  



  

    

    Rapids Logo

    

  



If your company uses Bokeh and is able to sponsor the project, please contact info@bokeh.org



*Bokeh is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides Bokeh with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit [numfocus.org](https://numfocus.org) for more information.*



*Donations to Bokeh are managed by NumFOCUS. For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax adviser about your particular tax situation.*



### In-kind Support



Non-monetary support can help with development, collaboration, infrastructure, security, and vulnerability management. The Bokeh project is grateful to the following companies for their donation of services:



* [Amazon Web Services](https://aws.amazon.com/)

* [GitGuardian](https://gitguardian.com/)

* [GitHub](https://github.com/)

* [makepath](https://makepath.com/)

* [Pingdom](https://www.pingdom.com/website-monitoring)

* [Slack](https://slack.com)

* [QuestionScout](https://www.questionscout.com/)

* [1Password](https://1password.com/)