US highschool performance Insights

Study of US/CA High School Performance and Socioeconomic Factors with SQL and GeoPandas

This project explores the relationship between high school performance and census data across different regions in the United States. By analyzing datasets containing information on high school academic proficiency and socioeconomic factors, we aim to uncover insights into educational outcomes and their broader context.

Overview

The project focuses on the following key aspects:

• Analyzing academic proficiency in math and reading across public high schools.
• Investigating correlations between high school performance and demographic indicators such as median household income and urbanization levels.
• Comparing educational outcomes across different states and regions.
• Visualizing findings and patterns with geospatial fata using choropleth maps.

Technologies Used

Python: Utilized for data analysis, manipulation, and visualization. SQL (Structured Query Language): Employed for querying and retrieving data from relational databases. GeoPandas: Used for handling geospatial data and creating geographical visualizations.