In the past two years, there has been incredible progress in Python data visualization libraries, particularly those built on client-side JavaScript tools such as D3 and Leaflet. This talk will give a brief demonstration of many of the newest charting libs: mpld3 (using Seaborn/ggplot), nvd3-python, ggplot, Vincent, Bearcart, Folium,and Kartograph will be used to visualize a newly-released USGS/FAA wind energy dataset (with an assist from Pandas and the IPython Notebook). After a demo of the current state of Python and web viz, it will discuss the future of how the Python data stack can have seamless interoperability and interactivity with JavaScript visualization libraries.

1. Up and Down the
Python Data &
Web Visualization
Stack

2. Hi. I’m Rob Story
wrobstory.github.io
https://github.com/wrobstory/pydatasv2014
@oceankidbilly

3. I work for DataPad
We’re building a visual data analytics platform. It’s awesome.
!
Sign Up: www.datapad.io
!
We’re Hiring!

4. Visualization in python
We’ve come a long way.

5. 2012
Matplotlib
Chaco
2014
Matplotlib
Bokeh
Vincent
Seaborn
ggplot
Vispy

6. “Why doesn’t everyone
work together to build one
python charting library?”
“Why doesn't everyone
work together to write one
programming language?”
=

7. choices are
signs of a
healthy ecosystem
We need more visualization
libraries, and they should be
opinionated

8. The future present
is web visualization

9. IPython =
Browser
javascript
languages

10. The New Stacks
ggplot
seaborn
matplotlib
Vincent
Bearcart Rickshaw
Folium

11. Demo

12. THE
FUTURE

13. Ipython
Julia R
Gadfly rCharts

14. IPython
Coms
+
Widgets
+
Visualization

15. Python
Backbone
D3

16. Sticky

18. Thank you!
questions?