Project
Overview
The Health Equity Tracker aims to give a detailed view of health outcomes by race, ethnicity, sex, socioeconomic status, and other critical factors. Our hope is that it will help policymakers understand what resources and support affected communities need to be able to improve their outcomes.
Technical Highlights
- •Built ETL data pipelines using Python and Pandas to extract, transform, and load maternal mortality data from multiple sources into BigQuery, streamlining data processing and analysis workflows.
- •Queried BigQuery data using SQL to identify health disparities across demographic groups and inform policy decisions.
- •Refactored visualization components from Vega to D3, reducing dependencies by 8.6% and decreasing package size by 30%, significantly improving application performance.
- •Integrated new public health datasets via React/TypeScript frontend, enhancing data visibility and accessibility.
Technologies
Playwright
Pytest
Python
Pandas
React
TypeScript
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