MUSA 550: Geospatial Data Science
Use Python to gather, visualize, and analyze geospatial data with an urban planning and public policy focus
Welcome!
This is our landing page for our Fall course MUSA 550: Geospatial Data Science with Python.
On the left handside, you will find information about the syllabus, assignments, lectures and other important material. New material will be added every week. This course goes at a relatively fast pace. Don’t fall behind.
Many many thanks to Nick Hand! who developed this entire website and codes.
- Assignment 5 is due December 5
- Assignment 6 is due December 12
- no grace period for the first part, which is the project proposal
- Final project due December 26
Twelfth class: Thursday November 21. - predictive modeling
Eleventh class: Thursday November 14. - Visualizing Large Datasets - Clustering
Tenth class: Thursday November 7. - Census API - Visualizing Large Datasets
Ninth class: Thursday October 31. Halloween!! - API, Web Scraping, Text Analytics
Eight class: Thursday October 24. - API, Web Scraping
Seventh class: Thursday October 17. Raster Analytics. Assignment 3. shapely shapely
Sixth class: Thursday October 10. - Choropleth and hexagon maps - quick review (lecture 4). Interactive maps with folium - refresh (lecture 4). OSM data, network modeling (lecture 5)
Fifth class: Thursday Sep 26. python basics: text input & output see additional exercises #3. Review visualization libraries. Geopandas (lecture 3). Choropleth and hexagon maps; interactive maps with folium (lecture 4).
Fourth class: Thursday Sep 19. More python basics on function definition. Visualization lecture (covering matplotlib, altair, seaborn, …) and introduction to geospatial data (lecture 3)
Third class: Thursday Sep 12. We continue discussing python basics (functions, loops, conditionals), and lecture 2 on visualization (covering matplotlib, altair, seaborn, …). You will also have a bit of time to work on Assignment-1 or ask questions related to that.
Second class: Thursday Sep 4. We continue on basics of python, and we start week 2 material (visualization). Assignment 1 will be assigned.
Several students were having issues installing mamba (or conda) and then the class environment. You can follow the instructions here Installation Setup Guide. Note that the environment.yml file can be found here. Download it to your computer, then install it following the instructions.