python for economists

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Here you can find useful materials for the Python for Economists course.

notebook

Block I: Python for economic data

Lecture 1: Setup & Python Syntax

Lecture 2: Data Structures & Object-Oriented Programming

Lecture 3: Pandas, APIs & Econometrics

Lecture 4: Visualisation, EDA & Dynamic Optimisation

Block II: Data collection from the web

Lecture 5: Web Scraping I: requests & BeautifulSoup

Lecture 6: Web Scraping II: Sessions, Headers & Selenium

Block III: NLP and Machine Learning for Text

Lecture 7: NLP: Text Representation

Lecture 8: Sentiment Analysis & Supervised ML for Text

Lecture 9: Machine Learning for Text & LLMs via API

extra materials

Extra L1: Reproducibility, Environments, and Research Pipelines File

Extra L2: Data Structures, Complexity, and Vectorization

Extra L3: Pandas Joins, Keys, and Data Integrity

Extra L4: Visualization, EDA, and How Plots Can Mislead

Extra L5: Web Scraping Robustness and HTML Fragility

Extra L6: APIs vs Scraping, Pagination, and Rate Limits

Extra L7: NLP Representation, Similarity, and What Bag-of-Words Misses

Extra L8: Sentiment, Topic Models, and Measurement Error

Extra L9: Prediction, Explanation, Causality

Extra: Research Design & Replication