Editing Matplotlib

[[File:Matplotlib-hist2d.png|right|500px]]
__NOTOC__
== Visualizing data with Matplotlib and Wiki-bios ==

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 be focusing on a dataset drawn from Wikipedia and , containing the names, birth dates, genders, article creation dates, and number of edits, of over 180,000 Wikipedia biography articles.

The dataset used here has been drawn from several sources. The list of biographies and the gender of the biography subjects comes from a datbase called [http://dbpedia.org DBpedia] that is a structured database built from Wikipedia. If determines if articles are biographies from the Wikipedia category system and it determines if the subjects are male or female primarily by looking at whether subject is referred to as ''he'' or ''she'' in the article. Birthdates for people are extracted from the data recorded in Wikipedia in the "infobox" sidebars common to many pages. Data on how people edit Wikipedia is merged onto this dataset from a separate collection of metadata of Wikipedia editing very similar to the one we built for Harry Potter articles the morning.

=== 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

=== Download and test the Matplotlib-with-Wiki-bios project ===

(Estimated time: 10 minutes)

After installing matplotlib, and downloading and unpacking the Wikibios bundle, move into that directory with '''cd'''.  You can test your installation by running '''python histograms.py'''.  If matplotlib is install correcting, a chart file named '''histograms.pdf''' will appear in the current directory.

Bundle with code for all platforms: http://mako.cc/teaching/2014/cdsw-autumn/wikibios.zip

=== 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://blog.olgabotvinnik.com/prettyplotlib/ prettyplotlib]: hip-aesthetic matplotlib plots
** [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]]
@@ Line 1: / Line 1: @@
 [[File:Matplotlib-hist2d.png|right|500px]]
 __NOTOC__
-== Getting Started ==
+== Visualizing data with Matplotlib and Wiki-bios ==
-Download the CDSW Matplotlib code from [https://github.com/makoshark/matplotlib-cdsw/archive/master.zip here] and unzip it on your machine.
-We will also need the data file that is [http://communitydata.cc/~mako/hp_wiki.tsv here]
-== 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'll be focusing on a dataset drawn from Wikipedia and , containing the names, birth dates, genders, article creation dates, and number of edits, of over 180,000 Wikipedia biography articles.
-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]].
+The dataset used here has been drawn from several sources. The list of biographies and the gender of the biography subjects comes from a datbase called [http://dbpedia.org DBpedia] that is a structured database built from Wikipedia. If determines if articles are biographies from the Wikipedia category system and it determines if the subjects are male or female primarily by looking at whether subject is referred to as ''he'' or ''she'' in the article. Birthdates for people are extracted from the data recorded in Wikipedia in the "infobox" sidebars common to many pages. Data on how people edit Wikipedia is merged onto this dataset from a separate collection of metadata of Wikipedia editing very similar to the one we built for Harry Potter articles the morning.
-=== 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 ===
@@ Line 33: / Line 19: @@
 * Exercise your creativity by making your own visualization
-# First plot: <tt>001-hello-plot.py</tt>
+=== Download and test the Matplotlib-with-Wiki-bios project ===
-# Subplots: <tt>002-subplots.py</tt>
-# Let's do something more interesting: <tt>003-plot-timeseries.py</tt>
+(Estimated time: 10 minutes)
-# Visit the [http://matplotlib.org/gallery.html Matplotlib gallery].
-# Make another kind of plot: <tt>004-plot-histogram.py</tt>
+After installing matplotlib, and downloading and unpacking the Wikibios bundle, move into that directory with '''cd'''.  You can test your installation by running '''python histograms.py'''.  If matplotlib is install correcting, a chart file named '''histograms.pdf''' will appear in the current directory.
-# 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.
+Bundle with code for all platforms: http://mako.cc/teaching/2014/cdsw-autumn/wikibios.zip
 === References ===
@@ Line 46: / Line 32: @@
 * [http://matplotlib.org/examples/index.html matplotlib Examples] (many, with source)
 * Other plotting resources
+** [http://blog.olgabotvinnik.com/prettyplotlib/ prettyplotlib]: hip-aesthetic matplotlib plots
 ** [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
@@ Line 61: / Line 48: @@
 [[File:Wikipedia.png|right|250px]]
-[[Category:CDSW]]