Welcome to this small Python site to evaluate the Upstart Macro Index (UMI) and some of the macro variables it correlates to.

This repository contains the following files:

• data_processing.ipynb - Code to import UMI and macro data into CSVs
• umi_correlation.ipynb - Code to evaluate the UMI and macro correlations using CSVs
• LICENSE - MIT License we released this repository under
• data/umi.csv - Data file as downloaded from Upstart's website
• data/umi_data.csv - Data file with UMI data slightly updated for easier handling
• data/macro_data.csv - Data with downloaded Macro data

You an run this environment online through the Binder system if you don't want to set up your own Jupyter enviroment.

If you want to edit any of the maco data, you will need to add a file named '.env' and set the variable FRED_API_KEY to your FRED API key. If you don't have one, you can get one here: https://fred.stlouisfed.org/docs/api/api_key.html . To learn more about loading environment variables into python, please see https://pypi.org/project/python-dotenv/. If you are okay with the existing data, just ignore the data_processing notebook and the umi_correlation notebook will work great.