Python Beginner Modules

We will be closely following the runestone tutorials and Schafer’s tutorials, found here and here. This is a rigorous introduction to Python that contains many computer-scientific concepts. While this may seem overkill to many current economists, it is undeniably the future of economic research and is heavily used at the frontier. From econometric methods using ML to large-scale empirical projects using big data, from advances in numerical methods in macro models to the usage of complexity theory in game theory, computer science (and I mean computer science, not programming) has become more than just a tool for economics. While an A in real analysis or measure theory is still what adcoms look for in a PhD application, a lot more work at the frontier and in the future will rely on a solid grasp of computer-scientific concepts. Not to mention, if you are not going into academia after all after finishing a PhD in economics, your career prospects would be far greater if you have a solid foundation in computer science. The returns on investment is also large: learning one language rigorously allows you to learn other languages very quickly in the future.

TIMELINE:

Quarter 1

  1. Simple Python Data (thinkcspy: Chp 1-2, Schafer: Video 1)

  2. Strings (thinkcspy: Chp 9, Schafer: Video 2), Integers (Schafer: Video 3)

  3. Lists, Tuples, and Sets; Comprehension (thinkcspy: Chp 10, Schafer: Video 4, 19, 20)

  4. Files and Dictionaries (thinkcspy: Chp 11-12, Schafer: Video 5)

  5. Selection (thinkcspy: Chp 7, Schafer: Video 6)

  6. Turtle Graphics (thinkcspy: Chp 3-4, 8, Schafer: Video 7)

  7. Functions (thinkcspy: Chp 6, Schafer: Video 8)

Quarter 2

  1. Modules (thinkcspy: Chp 5, Schafer: Video 9)

  2. Advanced List and String (Schafer: Video 20-22)

  3. os and Files (thinkcspy: Chp 11, Schafer: Video 23, 25)

  4. Exceptions (thinkcspy: Chp 13, Schafer: Video 31)

  5. Classes (thinkcspy: Chp 17-18, Schafer: Video 40-42)

  6. Data Task 1

Quarter 3

  1. Regular Expressions (py4e-int: Chp 12, Schafer: Video 30)

  2. Simple Web Scraping (py4e-int: Chp 13-14, Schafer: Video 46)

  3. Data Task 2

  4. Pandas Part 1 (httlads: Chp 4-6, Schafer: Video 128-129)

  5. Pandas Part 2 (httlads: Chp 4-6, Shcafer: Video 130-132)

  6. Data Task 3