# bokeh
**Repository Path**: hou305/bokeh
## Basic Information
- **Project Name**: bokeh
- **Description**: Interactive Data Visualization in the browser, from Python
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-03-02
- **Last Updated**: 2020-12-19
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## 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 over large or streaming datasets. Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.
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Conda |
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PyPI |
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Live Tutorial |
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*If you like Bokeh and would like to support our mission, please consider [making a donation](https://numfocus.org/donate-to-bokeh).*
Installation
------------
The easiest way to install Bokeh is using the [Anaconda Python distribution](https://www.anaconda.com/what-is-anaconda/) 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](https://docs.bokeh.org/en/latest/docs/user_guide/quickstart.html#quick-installation).
Resources
---------
Once Bokeh is installed, check out the [Getting Started](https://docs.bokeh.org/en/latest/docs/user_guide/quickstart.html#getting-started) section of the [Quickstart guide](https://docs.bokeh.org/en/latest/docs/user_guide/quickstart.html).
Visit the [full documentation site](https://docs.bokeh.org) to view the [User's Guide](https://docs.bokeh.org/en/dev/docs/user_guide.html) or [launch the Bokeh tutorial](https://mybinder.org/v2/gh/bokeh/bokeh-notebooks/master?filepath=tutorial%2F00%20-%20Introduction%20and%20Setup.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 [Developer Guide](https://docs.bokeh.org/en/latest/docs/dev_guide.html) and say hello on the [Zulip Chat for Developers](https://bokeh.zulipchat.com/).
Follow us
---------
Follow us on Twitter [@bokeh](https://twitter.com/bokeh)
Sponsors
--------
The Bokeh project is grateful for [individual contributions](https://numfocus.org/donate-to-bokeh) as well as sponsorship by the organizations and companies below:
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.*
Security
--------
To report a security vulnerability, please use the [Tidelift security contact](https://tidelift.com/security).
Tidelift will coordinate the fix and disclosure.