Lead Instructors: Jielu Zhang and Devika Jain
Date and Time: May 22nd, 9:00 am to 12: 00 am
Location: Room SB -12, CGIS Knafel Building, 1737 Cambridge Street, Cambridge MA
Objective: This workshop focuses on how to analyze and visualize health-related geospatial datasets using
Python and Google Colab. The workshop introduces practical tools and techniques for working
with individual-level health data, public contextual datasets, and spatial data layers. Attendees
will learn how to process, integrate, analyze, and map health data to address health geography
research questions.
Topics Covered:
1. Introduction to geospatial health data analysis and spatial thinking.
2. Foundations of spatial data processing using Google Colab and Python, including
GeoPandas, Shapely, and related packages.
3. Integration of individual-level health data, such as cardiac arrest records, with
neighborhood, demographic, and public health datasets, including the CDC Social
Vulnerability Index and American Community Survey datasets.
4. Spatial analysis of health-event patterns, neighborhood context, and healthcare access
(Automated External Defibrillator dataset).
5. Static and interactive visualization of health-related geospatial data.
Target Audience:
This workshop is designed for basic to intermediate level Python users. Basic Python programming
experience is required. Participants should be comfortable loading, inspecting, and cleaning CSV
files, and some experience with NumPy and Pandas is recommended but not required. The
workshop is suitable for researchers, students, and practitioners interested in health geography,
geospatial analysis, public health data, and spatial visualization using Python.
This workshop is free for Harvard affiliates with a valid Harvard ID, and is $100 for others.
How to Apply:
On these forms, make sure to choose Using Python for Geospatial Analysis and Visualization as the workshop name.