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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: 6 days ago
JSON representation

Interactive Data Visualization in the browser, from Python

Host: GitHub
URL: https://github.com/bokeh/bokeh
Owner: bokeh
License: bsd-3-clause
Created: 2012-03-26T15:40:01.000Z (almost 13 years ago)
Default Branch: branch-3.7
Last Pushed: 2025-01-09T23:09:04.000Z (17 days ago)
Last Synced: 2025-01-12T17:42:19.231Z (14 days ago)
Topics: bokeh, data-visualisation, interactive-plots, javascript, jupyter, notebooks, numfocus, plots, plotting, python, visualisation, visualization
Language: TypeScript
Homepage: https://bokeh.org
Size: 328 MB
Stars: 19,519
Watchers: 439
Forks: 4,201
Open Issues: 797
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE.txt
- Code of conduct: docs/CODE_OF_CONDUCT.md
- Security: docs/SECURITY.md

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README

----

[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

Project

Downloads

Build

Community

*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 [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/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 monetary support from the organizations and companies listed below:

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/)