Geography 385: Spatial Data Analysis

Home
Lectures
Studio
References

About

About

Weeks
- Week 1: 8-26, 8-28
  - Course Overview
  - Studio 1: Jupyter Hub
- Week 2: 9-04
  - Labor Day Holiday
  - Studio: Pandas
- Week 3: 9-09, 9-11
  - Spatial Data Analysis
  - Studio: GeoPandas
- Week 4: 9-16, 9-23
  - Methods for Area Unit Data
  - Studio: geosnap
- Week 5: 9-23, 9-25
  - Visualization for Area Unit Data
  - Studio: Choropleth Mapping
- Week 6: 9-30, 10-02
  - Spatial Weights
  - Studio 06 Peer Evaluation 1
- Week 7: 10-07, 10-09
  - Global Spatial Autocorrelation
  - Studio 07 Global Spatial Autocorrelation
- Week 8: 10-14, 10-16
  - Local Spatial Autocorrelation
  - Studio 08 Local Spatial Autocorrelation
- Week 9: 10-21, 10-23
  - Clustering and Regionalization in Geographic Data Science
  - Studio 09 Peer Evaluation 2
- Week 10: 10-27, 20-30
  - Point Pattern Basics
  - Studio 10 Geoprocessing Points
- Week 11: 11-04, 11-06
  - Centrography for Point Patterns
  - Quadrat Statistics
- Week 12: 11-11, 11-13
  - 11-11 Veteran's Day (Holiday)
  - Studio 11 Peer Evaluation 3
- Week 13: 11-18, 11-20
  - Nearest Neighbor Tests
  - Computational Essay Help Session
- Week 14: 11-25
  - Distance Based Methods
  - Thanksgiving Holiday (no class 11-27)
- Week 15: 12-02, 12-04
  - Distance Based Methods
  - Studio 12 Project Help
Resources
- Syllabus

About

Geography 385 Spatial Data Analysis is an introduction to exploratory spatial data analysis taught by Professor Sergio Rey at San Diego State University.

Source Code

---
title: About
---

Geography 385 Spatial Data Analysis is an introduction to exploratory spatial
data analysis taught by Professor Sergio Rey at San Diego State University.