Data Analysis Resources

Python Books

Here is a list of books related to data analysis that I have found useful in my class.

• Janert, P. K. (2011), Data Analysis with Open Source Tools, is my preferred book for teaching the basic concepts of data analysis. Available on-line through the Purdue library. Also available for download via IT eBooks.
• McKinney, W. (2012), Python for Data Analysis, introduces the Python Data Analysis Library (pandas) a very useful set of tools, especially for working with time series data. Available on-line through the Purdue library.

Statistical Tools

• Python based tools
  • SciPy - statistical analysis tools for science in Python - The Stats module in SciPy contains a large number of probability distributions and a growing library of statistical functions, especially for probability function study.
  • StatsModels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration.
  • Scikit-learn is a Python module for machine learning and data mining. Contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensional reduction.
• R Project for Statistical Computing
  • Free distribution that is installed on most Linux/Unix systems and is also available for other platforms. It is available through Anaconda.
  • Based on S-plus, an older proprietary statistical analysis package, the R-project is an example of open source software development driving a company out of business.
  • Introduction to R
  • RPy module for Python provides access to many R project statistical tools
• SAS statistical tools
  • Proprietary software package, available through Purdue University license for installation on University systems.
  • Information on licensing for faculty, staff and students can be found through the Purdue IT Software Licensing and Distribution page
  • SAS Tutorials for Statistical Data Analysis
• SPSS statistical tools
  • SPSS is favored by the social science research community.
  • Proprietary software package, available through Purdue University license for installation on University systems.
  • Information on licensing for faculty, staff and students can be found through the Purdue IT Software Licensing and Distribution page
  • Tutorial: Analyzing with SPSS Statistics - basic tutorial from IBM.
  • Here is a useful page on Social Science Data and Statistics Resources focused on SPSS from Tufts University.
  • Lots of other on-line courses available if you want to pay, including one through Purdue Global.

Environmental Metrics

• Literature on Metrics found to be Environmental Indicators
  • Streamflow Metrics
  • Spatial Metrics
• Tools for Calculating Metrics
  • USGS - R commands for calculating streamflow metrics

Tools for Working with Date and Time Information

• Shared Date and Time Tools - these libraries are now only supported for C language applications as datetime support is now well integrated into Python and its submodules.
• Python tools for working with date and time
  • Python datetime module
  • NumPy datetime64 data type
  • Working with date and time in pandas
• Working with date and time in the Generic Mapping Tools (GMT)

Tools for Working with Common Data Formats

• ASCII text files
  • Software packages
    • Excel
  • Python tools
    • Reading and Writing files in Python
    • Text read and write functions in NumPy
    • Text read and write functions in pandas 
• Binary files
• NetCDF files
• HDF and HDF5 files
• GRiB files

Graphical Analysis Tools

• Using matplotlib to create MatLAB like plots and graphical analysis
  • Pyplot tutorial - Limited tutorial, but method for importing pylab library makes understanding what is part of the module much easier.
  • A more complete tutorial - Assumes pyplot is a stand-alone module. As of February 10, 2014 you will need to import pylab using the command: "from matplotlib.pyplot import *" for the tutorial examples to work.
  • Gallery - Images of matplotlib figrues, and the source code use to make them.
• The PyGMT interface for the Generic Mapping Tools for processing geospatial and geophysical data and making publication-quality maps and figures without having to learn Linux.
• PyNGL is a Python interface to the high quality 2D scientific visualizations in the NCAR Command Language (NCL).

Geospatial Tools

• Working with Python in ArcGIS
• PyGMT interface for the Generic Mapping Tools
• PyQGIS scripting language for QGIS (Quantum GIS)

Other Tools

• Other Tools