Datavisiualization examples

We created several draft visualization lessons using ipython notebooks.   The lessons include python code to parse data and create plots and some explanation (how to explore data, when to use certain types of plots).   

A couple of caveats

1.  Examples were done by different people so both the writing and coding style may be a little different between examples. 
2.  We may have used inconsistent terminology in places. 
3.  Explanations are not complete. 

The following description of the work is copied from our index.md file.  

Datavisualization with Python and matplotlib

This lesson assumes that you already understand basic programming concepts and are either familiar with, or can quickly master, the basic elements of Python. In this lesson we visualize several types of health care data. We explain when to use different chart types.

1.  Health Indicators Scatterplot This example uses health indicators for NY-state (such as diabetes and cardiac event rates per county) to show how to graph relationships between 2 or 3 variables.

2.  Hospital Infections This example uses NY-State hospital infection counts to demonstrate compositions over a few time periods. The example compares yearly infection counts at two hospitals.
 
3.  FDA data This examples uses FDA adverse event data to show how to compare data. We compare categories of drugs using adverse events. Several cases are shown, ranging from few items and categories to many items and categories.

4. FDA data part 2 This example uses FDA adverse event data sampled on a weekly basis for many years. The data has a few hundred points. We use it to show how to plot near continuous data using line and area charts.

5. Sparcs This example uses another NY-State health dataset to illustrate histograms and pie charts.