In this tutorial, I review ways to take raw categorical survey data and create new variables for analysis and visualizations with Python using pandas and GeoPy. I’ll show how to make new pandas columns from encoding complex responses, geocoding locations, and measuring distances.
Here’s the associated GitHub repository for this workshop, which includes the data set and a Jupyter Notebook for the code.
Thanks to the St. Lawrence Eastern Lake Ontario Partnership for Regional Invasive Species Management (SLELO PRISM), I was able to use boat launch steward data from 2016 for this virtual workshop. The survey data was collected by boat launch stewards around Lake Ontario in upstate New York. Boaters were asked a series of survey questions and their watercrafts were inspected for aquatic invasive species.
This tutorial was originally designed for the Syracuse Women in Machine Learning and Data Science (Syracuse WiMLDS) Meetup group.