https://github.com/bokeh/bokeh-notebooks

Interactive Web Plotting with Bokeh in IPython notebook
https://github.com/bokeh/bokeh-notebooks

Last synced: about 2 months ago
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Interactive Web Plotting with Bokeh in IPython notebook

• Host: GitHub
• URL: https://github.com/bokeh/bokeh-notebooks
• Owner: bokeh
• License: bsd-3-clause
• Archived: true
• Created: 2014-07-07T16:42:49.000Z (about 10 years ago)
• Default Branch: main
• Last Pushed: 2023-10-20T02:04:34.000Z (11 months ago)
• Last Synced: 2024-06-11T19:20:57.953Z (4 months ago)
• Language: Jupyter Notebook
• Size: 77.7 MB
• Stars: 735
• Watchers: 71
• Forks: 665
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.txt

Awesome Lists containing this project

• awesome - bokeh-notebooks - Interactive Web Plotting with Bokeh in IPython notebook (Jupyter Notebook)

README

        
# THIS REPO IS OUTDATED. SEE https://github.com/bokeh/tutorial FOR UP TO DATE TUTORIALS

Bokeh in Jupyter Notebooks

==========================

Welcome to [Bokeh](https://bokeh.org/) in Jupyter Notebooks!

Bokeh is a Python interactive visualization library for large datasets that

natively uses the latest web technologies. Its goal is to provide elegant,

concise construction of novel graphics in the style of Protovis/D3, while

delivering high-performance interactivity over large data to thin clients.

These Jupyter notebooks provide useful Bokeh examples and a tutorial to get

started. You can download the repository and execute `jupyter notebook` from 

your terminal to try out the notebooks locally on your own machine.

Alternatively, you can immediately launch live versions of the Tutorial 

notebooks in your browser on [mybinder.org](https://mybinder.org/v2/gh/bokeh/bokeh-notebooks/master?filepath=tutorial%2F00%20-%20Introduction%20and%20Setup.ipynb).

Please visit the [Bokeh web page](https://bokeh.org) for

more information and full documentation, and the [Bokeh Discourse](https://discourse.bokeh.org/)

for community discussion.

Be sure to follow us on Twitter [@bokeh](https://twitter.com/bokeh)!