Data Viz in Pyton as a Tool to Study HIV Health Disparities

on YouTube ↗01h 07m

" summary

Python code uses Matplotlib, Seaborn, Plotly to turn Texas HIV records plus county health rankings into maps, bar charts and a correlation heatmap that finds household income correlation ~0.91 with viral suppression. The dataset shows African Americans account for about 37% of Texans living with HIV and Black women ~56% within some groups. The presenter builds reproducible Jupyter notebooks and an interactive dashboard prototype; a live quiz demo has connectivity hiccups but the visual analytics run and highlight actionable county targets.

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" chapters (8)

1. 0:00Data viz in public health
2. 3:34Talk objectives & quiz
3. 19:35Health disparities defined
4. 27:33HIV impact overview
5. 34:55Key Python libraries for health data visualization
6. 43:02Live coding: bar & line charts
7. 55:49Ethics in data viz
8. 1:03:13Q&A

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