Predicting Health with Data

I recently explored activity rate trends for Open Vial Issue, Stock-In, RI Vaccines, and Syringe usage across districts using Python (pandas + matplotlib) . To enhance visibility and interpretation: ✅ Bar colors were coded based on performance thresholds ✅ Data labels were added for clarity ✅ Charts were customized for readability Visualizing this data not only highlights underperforming areas (in red/yellow) but also makes it easier for stakeholders to identify where action is needed most. 📌 Tools used: Python, pandas, matplotlib 📂 Data Source: eVIN Export (UNDP project) Excited to keep diving deeper into healthcare analytics and using data to drive smarter decisions! 💡 #DataVisualization #Python #HealthcareAnalytics #DataScience #UNDP #PublicHealth #Matplotlib #Pandas

Personal Project | April 2025 ·   Developed an interactive dashboard to monitor inventory activity rates and stock movements. ·   Analyzed simulated inventory datasets using Power Query & SQL built visualizations in Power BI to track key metrics such as Activity rate, stockout frequency, and Indent shipment. ·   Implemented DAX calculations to measure count of inactive stores.