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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

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Interactive Data Visualization in the browser, from Python

Lists

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.



  Package



  

    Latest package version

  



  

    

    Supported Python versions

    

  



  

    

    Bokeh license (BSD 3-clause)

    

  



  Project



  

    Github contributors

  



  

    

    Link to NumFOCUS

    

  



  

    

    Link to documentation

    

  



  Downloads



  

    

    PyPI downloads per month

    

  



  

    

    Conda downloads per month

    

  



  

    

    NPM downloads per month

    

  



  Build



  

    

    Current Bokeh-CI github actions build status

    

  



  

    

    Current BokehJS-CI github actions build status

    

  



  

    

    Codecov coverage percentage

    

  



  Community



  

    

    Community support on discourse.bokeh.org

    

  



  

    

    Bokeh-tagged questions on Stack Overflow

     

  



  

    

    Follow Bokeh on Twitter

    

  



*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 `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 [launch the Bokeh tutorial](https://mybinder.org/v2/gh/bokeh/bokeh-notebooks/HEAD?labpath=index.ipynb) 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/branch-3.0/docs/CODE_OF_CONDUCT.md).*



## Follow us



Follow us on Twitter [@bokeh](https://twitter.com/bokeh)



## Support



### Fiscal Support



The Bokeh project is grateful for [individual contributions](https://opencollective.com/bokeh), as well as for 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 [email protected]



*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/)