Visualizing food network proximity across San Diego County.
Data Science Alliance • Food Network Dashboard
Python
Project Overview
Client | Feeding San Diego (Through the Data Science Alliance) |
Role | Data Analyst |
Timeline | 4 weeks (2025) |
Tools Used | Python, Plotly, Dash |
Background
Food insecurity response relies on dense networks of food pantries and partner agencies, yet a lack of spatial visibility into these networks can lead to service overlap, inefficiencies, and gaps in coverage. To address this, I worked with Feeding San Diego through the Data Science Alliance to analyze and visualize the geographic proximity of food distribution agencies across San Diego County.
As a data analyst, I processed and analyzed agency-level location and distance data to identify clusters of nearby providers and highlight areas of potential redundancy or isolation. I then built an interactive geospatial dashboard using Python, Plotly, and Dash that allows stakeholders to explore agency networks at varying distance thresholds and examine relationships between food banks and partner sites.
This project supported Feeding San Diego’s strategic planning efforts by translating complex spatial data into an accessible visualization, enabling more informed decisions around resource allocation, coordination, and equitable food access.