Editing Matplotlib (section)

== Visualizing data with Matplotlib  ==

In this session, we will explore how to produce clear, informative charts, graphs, and plots with [http://matplotlib.org/ Matplotlib], the most popular toolkit for scientific data visualization in Python.

We'll start with the data-set created [[Community_Data_Science_Workshops_(Fall_2015)/Day_3_Lecture|this morning]] containing information about edits to the Harry Potter Wikipedia article. 

We will then proceed to visualize different aspects of data from the [[Community_Data_Science_Workshops_(Fall_2015)/Day_2_Projects/Socrata|Socrata web API]].


=== Inspiration === 

* [https://flowingdata.com/ Flowing Data]
* [http://www-01.ibm.com/software/analytics/many-eyes/ Many Eyes]
* [http://www.edwardtufte.com/tufte/ Edward Tufte]
* [http://www.visualizing.org/ visualizing.org]
* [http://idl.cs.washington.edu/ UW Interactive Data Lab]

=== Goals ===

* Get set up to make graphs with Matplotlib
* Learn the basics of the Matplotlib API and workflow
* Practice reading the Matplotlib documentation
* Build a plotting program step by step
* Learn simple ways to distill the essence of a large data set
* Explore the art of visualizing data
* Exercise your creativity by making your own visualization

# First plot: <tt>001-hello-plot.py</tt>
# Subplots: <tt>002-subplots.py</tt>
# Let's do something more interesting: <tt>003-plot-timeseries.py</tt>
# Visit the [http://matplotlib.org/gallery.html Matplotlib gallery]. 
# Make another kind of plot: <tt>004-plot-histogram.py</tt>
# Dive deeper into web APIs: <tt>005-traffic-timeseries.py</tt>
# Play around with any/all the data you've seen! You can find some more examples in the <tt>wikibios</tt> folder.
 
=== References ===

* [http://matplotlib.org/api/pyplot_summary.html matplotlib API reference]
* [http://matplotlib.org/examples/index.html matplotlib Examples] (many, with source)
* Other plotting resources
** [http://web.stanford.edu/~mwaskom/software/seaborn/ Seaborn]: fancy matplotlib-based visualizations
** [http://ggplot.yhathq.com/ ggplot]: port of the R language's ggplot2 library to python
** [http://d3js.org/ D3.js]: interactive data visualization for the browser (javascript)

=== Example topics to cover in Lecture ===

* line charts
* histograms
* binning
* scatter plots
* heat maps
* axis labeling
* legends

[[File:Wikipedia.png|right|250px]]
[[Category:CDSW]]