This hands-on workshop covers analysis of spatial data using the Python programming language, open source tools, and public data.
Notebooks are presented as slides with the Jupyter extension RISE. To navigate the presentation, press Space (or PgDn) to proceed to the next slide, Shift-Space (or PgUp) to go backward, and Shift-Enter to execute a code cell.
Use these links to launch individual notebooks with Binder:
- Overview
- Introduction to Jupyter Notebooks and Python
- Python Data Types and Methods: Numeric Types, Strings
- Python Data Types and Methods: Lists, Tuples, Dictionaries and Arrays
- Programming Logic in Python - Part 1
- Programming Logic in Python - Part 2
- Processing Files using Iteration, Lists, Arrays, and pandas DataFrames
- Haversine Geographic Distance and Open Data APIs
- Spatial Databases with PostgreSQL and PostGIS
Binder launches sometimes fail. To run locally instead, install RISE and launch with the classic Jupyter Notebook. RISE is not currently compatible with JupyterLab.
The workshop material is heavily based on CP255: Urban Informatics and Visualization, a course at the University of California, Berkeley, Department of City and Regional Planning, with work by Professor Paul Waddell and others. Some resources are also based on Python and Jupyter documentation, as well as the books Python for Data Analysis by Wes McKinney and Think Python by Allen Downey.