FeaturedUdemy
Visualizing Geospatial Data in Python
4.8(342)22k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate Python course explores how to connect physical locations with geographic context using GeoPandas. Working with open data from the City of Nashville, you will practice spatial joins, mapping overlays, and spatial data analysis.
Who It's For
Data scientists and Python users looking to master spatial analysis and create compelling map-based data visualizations.
Key Takeaways
- GeoPandas Mastery: Construct geospatial visualizations and handle geographical datasets using the GeoPandas library.
- Spatial Joins & Overlays: Join datasets based on spatial location and overlay geospatial data onto base maps for contextual insights.
- Real-World Applications: Analyze open municipal datasets from Nashville to extract spatial patterns and public insights.
About this course
One of the most important tasks of a data scientist is to understand the relationships between their data's physical location and their geographical context. In this course you'll be learning to make attractive visualizations of geospatial data with the GeoPandas package. You will learn to spatially join datasets, linking data to context. Finally you will learn to overlay geospatial data to maps to add even more spatial cues to your work. You will use several datasets from the City of Nashville's open data portal to find out where the chickens are in Nashville, which neighborhood has the most public art, and more!
Price
Free
This course is free to enrol.
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