https://github.com/bokeh/bokeh-notebooks
Interactive Web Plotting with Bokeh in IPython notebook
https://github.com/bokeh/bokeh-notebooks
Last synced: 8 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 (over 11 years ago)
- Default Branch: main
- Last Pushed: 2023-10-20T02:04:34.000Z (about 2 years ago)
- Last Synced: 2024-10-29T21:58:58.844Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 77.7 MB
- Stars: 737
- Watchers: 71
- Forks: 671
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.txt
Awesome Lists containing this project
- awesome-jupyter - Interactive Web Plotting with Bokeh
- -awesome-jupyter - Interactive Web Plotting with Bokeh
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# THIS REPO IS OUTDATED.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)!