Python for Economists: An overview of Python tools for Economists
summary
Covers concrete tools and results: uses csv module to clean ~10,000 rows with 32 variables, fixes comma-in-name issues and computes 5‑year averages; uses xlrd for multi‑sheet Excel, pandas/numpy for fast aggregation, matplotlib for 3D production plots, NetworkX to build an NFL roster graph (2002–2014), scrapy to pull Russian Wikipedia word frequencies, and simpy to run a buyer‑seller market agent simulation that works for dozens to hundreds of agents but hits memory limits near 10,000.
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chapters (11)
- 0:00Introduction
- 0:52Economics and data analysis
- 2:24Python for economists
- 4:48Working with CSV data
- 11:17Handling Excel files
- 15:18Network analysis
- 18:53Data mining techniques
- 25:57Pandas and Numpy
- 29:35Data visualization
- 30:53Economic simulations
- 36:04Q&A and conclusion
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