Bokeh:
Interactive Data Visualizations with Python

PyLadiesATX

by Christine Doig

Introduction

About me

Data Scientist at Continuum Analytics

From Barcelona. Living in Austin, TX

Started M.S. in DM and BI, UPC-BCN

Previously, Process Engineer and Business Analyst

M.S. Industrial Engineering, UPC-BCN

Master Thesis at RWTH Aachen, E.ON Energy Research Center

http://chdoig.github.com

About Bokeh

Python interactive visualization library that targets modern web browsers for presentation
http://bokeh.pydata.org/en/latest/
@BokehPlots Bokeh organization

About this tutorial

Exercises

1 - Data exploration.ipynb
2 - Charts.ipynb
3 - Plotting.ipynb
4 - Models.ipynb
5 - Layouts.ipynb
6 - Embed.ipynb

Tutorial Setup


$ git clone https://github.com/chdoig/pyladiesatx-bokeh-tutorial

http://chdoig.github.io/pyladiesatx-bokeh-tutorial/#/

Tutorial Setup

Anaconda: Python + Conda + a bunch of packages

or

Miniconda: Python + Conda +


$ conda env create
$ source activate pyladies-bokeh


$ python -c "import bokeh.sampledata; bokeh.sampledata.download()"

Bokeh version: 0.9.0

Bokeh Setup


$ conda install bokeh

or


$ pip install bokeh

http://bokeh.pydata.org/en/latest/docs/quickstart.html#quick-installation

http://bokeh.pydata.org/en/latest/docs/installation.html

Exercise 1

1- Data exploration.ipynb

Charts

Resources

Exercise 2

2- Charts.ipynb

Plotting

Resources

Exercise 3

3- Plotting.ipynb

Models

Resources

Exercise 4

4- Plotting.ipynb

I/O

Resources

Plotting examples

Tools, Interactions, Layouts, Styling

Resources

Exercise 5

5- Layouts.ipynb

Embed

Resources

Exercise 6

6- Embed.ipynb

Compat

Resources

Summary

Questions?

Slides:
http://chdoig.github.com/pyladiesatx-bokeh-tutorial

Email: christine.doig@continuum.io

Twitter: ch_doig