Geospatial Data Science in Python
Syllabus
Schedule
Section 401
Section 402
Content
Assignments
Overview
Section 401
Section 402
Resources
GitHub
Canvas
Ed Discussion
8. Analyzing and Visualizing Large Datasets
Weekly Course Content
1. Exploratory Data Science in Python
2. Data Visualization Fundamentals
3. More Interactive Data Viz, Intro to Vector Data & GeoPandas
4. Geospatial Analysis & Mapping
5. More Geospatial Analysis: Street Networks and Raster Data
6. Web Scraping
7. Working with APIs
8. Analyzing and Visualizing Large Datasets
9. From Notebooks to the Web: Part 1
10. From Notebooks to the Web: Part 2
11. Clustering Analysis in Python
12. Predictive Modeling with Scikit-Learn, Part 1
13. Predictive Modeling with Scikit-Learn, Part 2
14. Advanced Raster Analysis
On this page
Recommended Readings
New Packages
Useful Links and Reference Materials
Week 8: Analyzing and Visualizing Large Datasets
Content for lectures 8A and 8B
View materials:
MUSA-550-Fall-2023/week-8
HTML slides:
Lecture 8A
Lecture 8B
Executable slides:
Lecture 8A
Lecture 8B
Recommended Readings
Understanding the datashader algorithm
New Packages
intake
dask
datashader
colorcet
Useful Links and Reference Materials
Datashader User Guide
Datashader Example Use Cases
7. Working with APIs
9. From Notebooks to the Web: Part 1