Matplotlib: Difference between revisions

Latest revision as of 18:22, 7 May 2016

Getting Started[edit]

Download the CDSW Matplotlib code from here and unzip it on your machine.

We will also need the data file that is here

Visualizing data with Matplotlib[edit]

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

We'll start with the data-set created this morning containing information about edits to the Harry Potter Wikipedia article.

We will then proceed to visualize different aspects of data from the Socrata web API.

Inspiration[edit]

Goals[edit]

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

References[edit]

matplotlib API reference
matplotlib Examples (many, with source)
Other plotting resources
- Seaborn: fancy matplotlib-based visualizations
- ggplot: port of the R language's ggplot2 library to python
- D3.js: interactive data visualization for the browser (javascript)

Example topics to cover in Lecture[edit]

line charts
histograms
binning
scatter plots
heat maps
axis labeling
legends

@@ Line 1: / Line 1: @@
 [[File:Matplotlib-hist2d.png|right|500px]]
 __NOTOC__
-== Visualizing data with Matplotlib and Wiki-bios ==
+== Getting Started ==
+Download the CDSW Matplotlib code from [https://github.com/makoshark/matplotlib-cdsw/archive/master.zip here] and unzip it on your machine.
-In this project, 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 will also need the data file that is [http://communitydata.cc/~mako/hp_wiki.tsv here]
-We'll be focusing on a dataset drawn from Wikipedia and [http://dbpedia.org DBpedia], containing the names, birth dates, genders, article creation dates, and number of edits, of over 180,000 Wikipedia biography articles.
+== 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 ===
@@ Line 17: / Line 33: @@
 * Exercise your creativity by making your own visualization
-=== Download and test the Matplotlib-with-Wiki-bios project ===
+# First plot: <tt>001-hello-plot.py</tt>
+# Subplots: <tt>002-subplots.py</tt>
-(Estimated time: 10 minutes)
+# Let's do something more interesting: <tt>003-plot-timeseries.py</tt>
+# Visit the [http://matplotlib.org/gallery.html Matplotlib gallery].
-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.
+# 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://mako.cc/teaching/2014/cdsw-autumn/wikibios.zip Wikibios bundle for all platforms]
+* [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 36: / Line 61: @@
 [[File:Wikipedia.png|right|250px]]
+[[Category:CDSW]]