Course description¶
Data visualization is crucial for understanding geographical phenomena, and statistical thinking is essential for effective visualization. This course offers students a comprehensive understanding of geospatial data visualization and analysis techniques. Students will develop a strong foundation in statistical methods and spatial thinking abilities while learning to create compelling visualizations using Python. Key topics include statistical patterns, point patterns, areal patterns, and geovisualization. Through hands-on experience with Python libraries, students will enhance their spatial data science skills. By the end of the course, students will be well-equipped to analyze, visualize, and communicate geospatial data insights effectively.
Learning outcomes¶
Master statistical and spatial thinking for geospatial data visualization---thinking statistically while doing geovisualization.
Understand and apply key concepts such as statistical, point, and areal patterns.
Gain hands-on experience with Python libraries for data visualization and analysis.
Learn to create compelling visualizations to effectively communicate spatial data insights.
Licensing¶
Course content (text, images, figures, explanations)
© 2025 National University of Singapore.
Licensed under the Creative Commons
Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY-NC-ND 4.0).
You may share the material with attribution, but you may not modify it or use it commercially.
Code cells and example scripts
Code snippets and examples in this book are licensed under The MIT License.
You are free to reuse, modify, and distribute the code with attribution.