Teaching

Table of Contents

• ECON 481
  • Lectures
  • Problem Sets
  • Data
• ECON 487
  • Lectures

ECON 481

Syllabus

Lectures

Many lectures make use of Wes McKinney’s great book Python for Data Analysis, and I am greatly indebted to him. The Julia lecture makes use of Julia for Data Science by Jose Storopoli, Rik Huijzer and Lazaro Alonso.

0. Introduction to ECON 481 reveal.js¹
1. Introduction to Python and Git reveal.js
2. Numerical Computing in Python reveal.js
3. pandas reveal.js
4. Modeling and Data Visualization reveal.js
5. Web Scraping reveal.js
6. Writing Modules and Testing reveal.js
7. SQL reveal.js
8. R reveal.js
9. Julia reveal.js

Problem Sets

1. Problem Set 1 (Tests)
2. Problem Set 2 (Tests)
3. Problem Set 3 (Tests)
4. Problem Set 4 (Tests)
5. Problem Set 5 (Tests)
6. Problem Set 6 (Tests)

Data

• EPA data on greenhouse gas emissions for the last four years and parent companies²: 2022 xlsx 2021 xlsx 2020 xlsx 2019 xlsx Parent Companies xlsb
• NBA shots taken in games on 3/21/2022³: csv
• Apple daily stock price, 3/27/2023-3/25/2024⁴: html
• Gunnar Henderson’s Baseball Reference Page⁵: html
• Minute-level data on Apple stock price, 4/5/2024⁶ json
• Tesla daily stock price, 6/29/2010-4/15/2024⁷ csv
• Assorted auctions database with item description and bids⁸ db
• Historical polling data on U.S. Senate races in 2018, 2020, and 2022⁹ csv

ECON 487

Lectures

1. Bandit Algorithms reveal.js

Footnotes

1. I export the files to HTML. If you’d like a PDF version, see Quarto’s documentation.

2. Courtesy of the Environmental Protection Agency

3. Courtesy of Kaggle User bhavya

4. Courtesy of Yahoo! Finance

5. Courtesy of Baseball Reference

6. Courtesy of MarketWatch

7. Courtesy of Yahoo! Finance

8. Courtesy of ShopGoodwill.com

9. Courtesy of FiveThirtyEight