COGS108 Data Science Project (2022)

Conducted an in-depth analysis of the correlation between the Air Quality Index (AQI) and changes in driving patterns during the COVID-19 pandemic, leveraging Python, Pandas, NumPy, and Jupyter Notebooks

• Collected and meticulously cleaned large datasets on AQI and traffic patterns from multiple sources, ensuring accuracy and consistency over a 3-month period
• Applied statistical and data science techniques to uncover significant trends and insights, demonstrating the impact of reduced vehicular traffic on air quality

Overivew of this Project:

Research Question

Did California Air Quality significantly improve in different areas due to the COVID-19 Pandemic and the change in car traffic volume?

Hypothesis

We hypothesize that COVID-19 has had an overall good effect from 2020-2022 on Air Quality based on AQI (Air Quality Index). We think that the pandemic has led to more WFH (work-from-home) and remote opportunities for the general population of California, thus changing the amount of air pollution caused by a reduction in car traffic via commuting. We acknowledge that there may be some confounding variables including regional industries, population per capita, and lockdown restrictions