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bokeh-notebooks

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Interactive Web Plotting with Bokeh in IPython notebook

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# THIS REPO IS OUTDATED.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)!

bokeh-notebooks

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