Advanced Urban Analytics
This course series takes a computational social science approach to working with urban data.
https://github.com/gboeing/ppde642
Category: Sustainable Development
Sub Category: Education
Keywords
cities city-government coding course course-materials data-science jupyter network-analysis python spatial-analysis statistics syllabus transport transportation urban-analytics urban-data-science urban-informatics urban-planning urbanism usc
Keywords from Contributors
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Last synced: about 15 hours ago
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Repository metadata
USC urban data science course series in Python
- Host: GitHub
- URL: https://github.com/gboeing/ppde642
- Owner: gboeing
- License: mit
- Created: 2015-09-01T19:59:59.000Z (over 9 years ago)
- Default Branch: main
- Last Pushed: 2025-04-14T17:59:06.000Z (12 days ago)
- Last Synced: 2025-04-19T14:09:55.861Z (8 days ago)
- Topics: cities, city-government, coding, course, course-materials, data-science, jupyter, network-analysis, python, spatial-analysis, statistics, syllabus, transport, transportation, urban-analytics, urban-data-science, urban-informatics, urban-planning, urbanism, usc
- Language: Jupyter Notebook
- Homepage: https://geoffboeing.com
- Size: 415 KB
- Stars: 1,280
- Watchers: 120
- Forks: 488
- Open Issues: 1
- Releases: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
README.md
PPDE642: Advanced Urban Analytics
This is the second part of a two-course series on urban data science that I teach at the University of Southern California's Department of Urban Planning and Spatial Analysis.
This course series takes a computational social science approach to working with urban data. It uses Python and Jupyter notebooks to introduce coding and statistical methods that students can reproduce and experiment with in the cloud. The series as a whole presumes no prior knowledge as it introduces coding, stats, spatial analysis, and applied machine learning from the ground up, but PPDE642 assumes you have completed PPD534 or its equivalent.
Urban Data Science course series
PPD534: Data, Evidence, and Communication for the Public Good
The first course in the series, PPD534, starts with the basics of coding with Python, then on to data loading and analysis, then on to descriptive statistics, then inference and the scientific method, and finally a critical assessment of smart cities and urban informatics.
PPD534's lecture materials are available on GitHub and interactively on Binder.
PPDE642: Advanced Urban Analytics
The second course, PPDE642, assumes you have completed PPD534 (or its equivalent) and builds on its topics. It introduces spatial analysis, network analysis, spatial models, and applied machine learning. It also digs deeper into the tools and workflows of urban data science in both research and practice.
PPDE642's lecture materials are available in this repo and interactively on Binder.
Not a USC student?
Did you discover this course on GitHub? Come study with us: consider applying to the urban planning master's or PhD programs at USC.
Are you interested in data science and spatial analysis to improve urban transportation around the world, critically interrogate how big data reshapes housing affordability, or leverage technology for better city planning? We seek students from all backgrounds. If you're an activist or urbanist with no tech experience, we will teach you data/tech skills to effectively apply your knowledge to serve the community. If you're a coder or scientist interested in urbanism and planning, we will teach you how to unlock your skills for more equitable cities.
Owner metadata
- Name: Geoff Boeing
- Login: gboeing
- Email:
- Kind: user
- Description: Urban planning professor at USC: urban analytics, street networks, rental markets, data science.
- Website: https://geoffboeing.com/
- Location: Los Angeles, California
- Twitter: gboeing
- Company: University of Southern California
- Icon url: https://avatars.githubusercontent.com/u/4977197?u=53b802c4f37bf6e11a731113429ea9c756570217&v=4
- Repositories: 60
- Last ynced at: 2023-04-09T13:53:23.099Z
- Profile URL: https://github.com/gboeing
GitHub Events
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- Push event: 2
- Fork event: 2
Last Year
- Watch event: 18
- Push event: 2
- Fork event: 2
Committers metadata
Last synced: 5 days ago
Total Commits: 198
Total Committers: 2
Avg Commits per committer: 99.0
Development Distribution Score (DDS): 0.01
Commits in past year: 5
Committers in past year: 2
Avg Commits per committer in past year: 2.5
Development Distribution Score (DDS) in past year: 0.2
| Name | Commits | |
|---|---|---|
| Geoff Boeing | b****g@u****u | 196 |
| dependabot[bot] | 4****] | 2 |
Committer domains:
- usc.edu: 1
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 16
Total pull requests: 30
Average time to close issues: 3 months
Average time to close pull requests: 7 days
Total issue authors: 10
Total pull request authors: 3
Average comments per issue: 1.56
Average comments per pull request: 0.03
Merged pull request: 28
Bot issues: 0
Bot pull requests: 3
Past year issues: 0
Past year pull requests: 1
Past year average time to close issues: N/A
Past year average time to close pull requests: 33 minutes
Past year issue authors: 0
Past year pull request authors: 1
Past year average comments per issue: 0
Past year average comments per pull request: 0.0
Past year merged pull request: 1
Past year bot issues: 0
Past year bot pull requests: 1
Top Issue Authors
- kreamas (2)
- eccc-Antoine (2)
- Leuvtern (2)
- MartijnVerhoeven (2)
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Top Pull Request Authors
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- dependencies (3)
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Score: 7.848543482456679