Python

Overview

The power, speed, and versatility of Python and its body of packages make it an increasingly useful tool for those working with macroeconomic data. I’ve written a few examples of how this open-source programming language can be used to work with real-world economic data.

The Anaconda distribution of Python, which already includes key packages (such as NumPy, Pandas, SciPy, etc) and tools (Jupyter notebook, Conda), makes getting started, especially on a windows system, much easier.

Guides: Python for Macroeconomic Analysis

IMF API

Three-part guide to using the International Monetary Fund's Application Programming Interface to machine-read data.

NetworkX

Analyze and visualize the full trade network for goods using a few basic algorithms from the NetworkX package.

BLS API

A guide to collecting data from the U.S. Bureau of Labor Statistics API using Python's requests package.