Geospatial Data Science in Python
Syllabus
Schedule
Section 401
Section 402
Content
Assignments
Overview
Section 401
Section 402
Resources
GitHub
Canvas
Ed Discussion
6. Web Scraping
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 6: Getting Data, Part 1: Web Scraping
Content for lectures 6A and 6B
View materials:
MUSA-550-Fall-2023/week-6
HTML slides:
Lecture 6A
Lecture 6B
Executable slides:
Lecture 6A
Lecture 6B
Recommended readings
BeautifulSoup and CSS Selectors
Web scraping: a promising tool for geographic data acquisition
Web scraping in the news
OpenAI sued by authors (AP News)c
Scraping the Web Is a Powerful Tool. Clearview AI Abused It (Wired)
Web scraping is legal, US appeals court reaffirms (Techcrunch)
New Packages
Requests
Beautiful Soup
Selenium
Useful Links and Reference Materials
Insights into Housing Markets from Scraping Craigslist
and accompanying academic article
HTML tutorial
sections: introduction, basics, elements, attributes
Tutorial on Web Scraping with Requests and BeautifulSoup
CSS Selectors
5. More Geospatial Analysis: Street Networks and Raster Data
7. Working with APIs