#!/usr/bin/env python
# coding: utf-8

# <div>
# <a href="https://bokeh.org/"><img src="https://bokeh.org/img/hero.png"></a>
# </div>

# Welcome to [Bokeh](https://bokeh.org) in the Jupyter Notebook!
# 
# Bokeh is a Python interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of novel graphics in the style of D3.js, and to extend this capability with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.

# ## Quickstart
# 
# Get started with a [5-min introduction to Bokeh](quickstart/quickstart.ipynb).

# ## Tutorial
# 
# Start with the [Introduction and Setup](tutorial/00%20-%20Introduction%20and%20Setup.ipynb) notebook and jump to any of the specific topic sections from there.

# ## More information
# 
# Find more details and contact information at https://bokeh.org.
# 

# ## Thanks
# 
# Bokeh was originally developed with financial support from [Anaconda, Inc.](https://anaconda.com) and the Darpa XDATA initiative, and continues due to support from NumFOCUS and individual community contributions. Many thanks to [all of the Bokeh Github contributors](https://github.com/bokeh/bokeh/graphs/contributors).

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