QuantEcon DataScience

Introduction to Economic Modeling and Data Science


This section of the workshop covers data ingestion, cleaning, manipulation, analysis, and visualization in Python

We build on the skills learned in the Python fundamentals section and teach the pandas library

At the end of this section, you will be able to

  • Access data stored in a variety of formats
  • Combine multiple datasets based on observations that link them together
  • Perform custom operations on tables of data
  • Use the split-apply-combine method for analyzing sub-groups of data
  • Automate static analysis on changing data
  • Produce publication quality visualizations

In the end, our goal with this section is to give you the skills necessary to – at a minimum – immediately replicate your current data analysis workflow in Python with no loss of total (computer + human) time

This is a lower bound on the benefits you should expect to receive by studying this section

The expression “practice makes perfect” is especially true here

As you work with these tools, both the time to write and the time to run your programs will fall dramatically


Launch Notebook