Resources developed by @drewlevitt and @pksohn (drawing heavily from @gboeing's https://github.com/gboeing/urban-data-science) for a crash course in Python programming.
Topics include:
- essential programming concepts
- syntax and logic
- the pandas library for working with tabular data
- case study: analyzing trip distances with the California Household Travel Survey
- case study: geocoding street addresses using the Google Maps Geocoding API
Initially presented for students in CP 201B Planning Methods Gateway II, UC Berkeley Department of City and Regional Planning, April 2016. Refreshed for CP 201A in Fall 2016 using California Household Travel Survey, which is available here.