Visualizing the 2019 Measles Outbreak in NYC (with Python)
summary
Creates concrete visual evidence: pulls NYC Health Department tables and reproduces counts (1,250 US cases, 649 in NYC), cleans CSVs, and builds a month-by-month bar chart and a labeled bubble map of neighborhoods. Uses Python with bokeh and matplotlib, saves PNG/SVG outputs, and tunes bubble sizes and label offsets by hand so the static map reads without interaction. Shows bar numbers, percentages, and the April policy timing; the visuals work and match reported totals.
AI-written summary · about
chapters (9)
- 0:00Introduction
- 3:55Measles outbreak context
- 14:53First bar chart
- 29:20Improving visualizations
- 40:48Age group breakdown
- 56:50Vaccination status chart
- 1:05:02NYC outbreak map
- 1:17:25GitHub page results
- 1:22:09Q&A
related talks
42mVisualizing COVID-19 Data
07mNew York City weathers pandemic with data-first response
01h 07mData Viz in Pyton as a Tool to Study HIV Health Disparities
50mReporting on and visualising the pandemic
01h 01mVisualizing and Analyzing Data in 3D
26mSankey Plots with Python
36mBokeh Maps - Interactive Map for Your Next Web Application
21mTracking COVID 19 with Ruby