Pollution Factors and Wage Growth by Industry

This project downloads, parses, cleans, and analyzes EPA pollution factors, US Census Bureau GDP, and County Business Patterns data for 2017-2021. The current scope is analysis of pollution emissions by industry and analysis of wage growth within polluting industries.

Pre-requisites

Local deployment can be accomplished by creating a virtual environment using Python 3.11 and installing the necessary dependencies as described below.

Install dependencies from the terminal using the following command: pip install -r requirements.txt

OR

• Python 3.11
• Jupyter notebook 6.5.4
• API key

The following third party Python libraries were used:

• requests 2.31.0
• NumPy 1.26.4
• Pandas 2.2.1
• Matplotlib 3.8.3
• Seaborn 0.13.2

County Business Pattern data was accessed by API. Documentation for the US Census Bureau API can be found at https://www.census.gov/data/developers/guidance/api-user-guide.html.

Getting Started

To run this project, download and unzip the following files:

1. datasets.zip (Contains the below csv files)
   • 2012_to_2017_NAICS.csv
   • all_geocodes_v2021.csv
   • CAP_HAP_national_2017_v0.1_864d573.csv
   • CRHW_national_2017_v0.1_864d573.csv
   • SAGDP2N__ALL_AREAS_1997_2022.csv
   • SupplyChainGHGEmissionFactors_v1.2_NAICS_CO2e_USD2021.csv
2. pollution_and_wages.ipynb (Project notebook)

Open the .ipynb file in Jupyter Notebook and run the code to download, parse, clean, and analyze the raw US Census Bureau and EPA data.

Support

Contributions and suggestions are welcome and may be submitted by forking this project and submitting a pull request through GitHub.