Python makes it easy to retrieve and analyze economic data. These tutorials show how to access data from major sources—IMF, BLS, and Census—using open-source libraries. Additional guides covering other economic data APIs are available in the econ_data/APIs section of my GitHub.
I recommend the miniconda distribution of Python, which includes Python, Conda (package manager), and pip. You can then install packages like NumPy, Pandas, and Jupyter with conda install.
Access international economic data from the International Monetary Fund (IMF). Covers GDP, trade, prices, and more for 190+ countries.
Retrieve national accounts data from the Bureau of Economic Analysis including GDP, consumer spending, and industry statistics.
Retrieve US labor statistics—employment, wages, prices—directly from the Bureau of Labor Statistics (BLS) API.
Read and analyze Current Population Survey microdata with Python. Build custom labor market statistics from household-level data.
Retrieve US economic indicators from the Census Bureau, including retail sales, international trade, construction, and manufacturing.
Access federal finance data including revenue, spending, and debt from the US Treasury Fiscal Data API.