Notebooks

Data management and analysis in Python

This is a collection of IPython notebooks demonstrating a variety of techniques for data management and analysis.

This page mainly contains links to the notebooks. More detailed information about the various analyses is contained in the notebooks themselves.

US 2012 Medicare payment data

The data can be obtained here. The first script below can be used to produce state-level data files that are used in the subsequent scripts.

• Subset data by state

• Identify high payment providers

• Compare provider types by state

• Associations between provider type and service type

Comparison of gene expression in ulcerative colitis and Chron's disease patients

The data are available from the NCBI Gene Expression Omnibus (GEO) here.

• [Differential expression analysis] (http://nbviewer.ipython.org/github/kshedden/python-workshop/blob/master/GDS1615/differential_expression.ipynb)

Analysis of nation-level fertility trends

The data are available from the World Bank here.

• [PCA] (http://nbviewer.ipython.org/github/kshedden/python-workshop/blob/master/WB-Fertility/WB_fertility_factor.ipynb)

National Health and Nutrition Examination Survey (NHANES)

The data are available from the NHANES web site: http://www.cdc.gov/nchs/nhanes.htm

• Scatterplot smoothing

• Linear regression