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Using Python to Streamline Regional Land Use and Parcel Data Processing

Presenter(s):  Kurt Cotner

Abstract: Among some of the most critical datasets MAG produces are Regional Land Use and a set of Parcel Information Tables, which detail residential and non-residential building space across the region.  These datasets serve as key inputs for socioeconomic modeling and analysis.  In an effort to meet increasing demands for timely and accurate data, Python programming is utilized to automate the bulk of the processing on these very large datasets.   In concert with ArcPy, the Pandas data analysis library proved to be instrumental in streamlining the production of these datasets and improving their quality.

Key Takeaway: Python is an extremely powerful and flexible tool that can help to automate and organize complex projects, especially when working with very large data sets.

Intended Audience: Data analysts, programmers, land use planners

About the presenter(s):

Kurt Cotner is a GIS Analyst with the Maricopa Association of Governments in Phoenix, where he works primarily on the preparation and analysis of regional existing and future land use datasets.  In addition to working at MAG, he is currently pursuing a Master's degree in Business Analytics at GCU.