arielgoldszmidt/comp-econ-sp18

Main Course Repository for Computational Methods in Economics (Econ 21410, Spring 2018)

ECON 21410: Computational Methods in Economics

Syllabus

The full class syllabus can be found here.

• Class: Tuesdays and Thursdays, 3:30 - 4:50 PM in SHFE 103
• TA Session: Mondays 7:30-8:30 PM in SHFE 103
• Lecturer: Jeremy Bejarano, [email protected]
• Office Hours: by appointment
• Teaching Assistant: Philip Xinyu Cao, [email protected]
• TA Office Hours: Mondays, 1:45-2:45, in the graduate commons (SHFE 201)
• Website: Canvas will be used for grades. Homeworks and notes will be posted on the course GitHub repo: https://github.com/jmbejara/comp-econ-sp18

Notes

There should be about 19 classes and 9 TA sessions (first Monday excluded). This means that we have 28 in-class sessions total before the reading period.

• We will have one midterm. It will take place on Monday, April 30 during the regularly scheduled TA session, 7:30-8:30 PM in SHFE 103.
• Read the lectures ahead of time. The lectures (from, e.g., QuantEcon or the Python Data Science Handbook) have hyperlinks to the appropriate text.
• Solutions to the homework will be posted in a separate GitHub repo, found here: https://github.com/econ-21410-sp18/comp-econ-hw-jbejarano1

Books Used

• Lectures in Quantitative Economics, by Thomas J. Sargent and John Stachurski (QuantEcon)
• Python Data Science Handbook, by Jake VanderPlas (PDSH)
• Python for Data Analysis, 2nd Edition, by Wes McKinney (PDA)

Assignments

• Assignments must be turned in before midnight on the day that they are due. This means that you must submit your pull request on GitHub at 11:59pm or earlier on the due date (usually a Monday). Late assignments will not be accepted.

Schedule

Introduction to Python, Git, and GitHub

• Class 1: Tuesday, March 27
  • Introduction and Course Overview
    • Review syllabus. Talk about course content.
    • Demonstrate how course will be using GitHub. Show how to download assignments. Full Git tutorial will be next class.
    • Establish times for TA Sessions and for Python Crash Course
  • Go over points from Gentzkow and Shapiro’s Practitioner’s Guide
  • QuantEcon: "About Python"
    • Include demos. These should include interactive plots, widgets, LaTeX
  • Python Basics Pretest (in class assessment)
    • I will be holding a few hours of lectures on Saturday to go over “A Whirlwind Tour of Python.” I will help students with the assignment.
  • Distribute Assignment 0
    • You can find HW 0 here.
• Class 2: Thursday, March 29
  • Do Before Class:
    • Download GitKraken
    • Watch the following two YouTube videos about Git:
      • https://www.youtube.com/watch?v=K0mgc3efx-A
      • https://www.youtube.com/watch?v=M-O8ZNW9icQ
  • "QuantEcon: “An Introductory Example"
  • Git, GitHub, and GitHub Classroom
    • Go over how we will be using Git and GitHub in this class.
    • Download GitKraken. Do in-class Git assignment
    • Demonstrate GitHub README system. Teach basics of Markdown
• Python Crash Course: Saturday, March 31.
  • Work through QuantEcon: "Python Essentials"
  • Saturday, March 31 from 12-2pm in Saieh 146.
• Class 2a: Monday, April 2
  • QuantEcon: "Setting up Your Python Environment"
  • Due: Assignment 0
  • Distribute Assignment 1
    • Practice with Numpy, SciPy, and Matplotlib
• Class 3: Tuesday, April 3
  • QuantEcon: "Numpy"
  • QuantEcon: "Matplotlib"
• Class 4: Thursday, April 5
  • QuantEcon: "SciPy"
• Class 4a: Monday, April 9
  • QuantEcon: "Object Oriented Programming I"
  • QuantEcon: "Object Oriented Programming II"
  • Due: Assignment 1
  • Distribute Assignment 2
    • Pandas Basics

Data Wrangling with Python

• Class 5: Tuesday, April 10
  • Introduction to Pandas
• Class 6: Thursday, April 12
  • Quandl
  • Introduction to Pandas, continued
  • In-Class Exercise (occupations notebook)
  • PDSH: "Handling Missing Data" (read on your own)
• Class 6a: Monday, April 16
  • Go over any questions from HW 2
  • PDSH: "Hierarchical Indexing"
  • Due Assignment 2
  • Distribute Assignment 3
    • Data Munging with Pandas
• Class 7: Tuesday, April 17
  • PDSH: "Combining Datasets: Concat and Append"
  • PDSH: "Combining Datasets: Merge and Join"
  • PDA: "Data Loading, Storage, and File Formats"
  • QuantEcon: Writing Good Code (Read on your own)
• Class 8: Thursday, April 19
  • PDSH: "Aggregation and Grouping"
  • PDSH: "Pivot Tables"
  • PDSH: "High-Performance Pandas: eval() and query()"
• Class 8a: Monday, April 23
  • PDSH: "Vectorized String Operations"
  • Due Assignment 3
  • Distribute Assignment 4
    • Summarizing and Visualizing Data
• Class 9: Tuesday, April 24
  • PDSH: "Working with Time Series"
  • PDSH: "Further Resources" (Read on your own.)
• Class 10: Thursday, April 26
  • Data visualization with Python
• Class 10a: Monday, April 30
  • Midterm
  • In-Class midterm, starts at 7:30. You will need to bring your laptop with you to complete the midterm. The midterm will be similar to the HW assignments.signments.

Econometrics with Python (and R)