30-days Money-Back Guarantee
Vector data analysis in Python with GeoPandas, statsmodels, and Scikit-learn
Updated on Sep, 2026
Programming, Data Science, Machine Learning
Training 5 or more people ?
Get your team access to 10000+ top Tutorials Point courses anytime, anywhere.
In this course, I demonstrate open-source Python packages for the analysis of vector-based geospatial data. I use Jupyter Notebooks as an interactive Python environment. GeoPandas are used for reading and storing geospatial data, exploratory data analysis, preparing data for use in statistical models (feature engineering, dealing with outlier and missing data, etc.), and simple plotting. Statsmodels is used for statistical inference as it provides more detail on the explanatory power of individual explanatory variables and a framework for model selection. Scikit-learn is used for machine learning applications as it includes many advanced machine learning algorithms, as well as tools for cross-validation, regularization, assessing model performance, and more.
This is a project-based course. I use real data related to biodiversity in Mexico and walk through the entire process, from both a statistical inference and machine learning perspective. I use linear regression as the basis for developing a conceptual understanding of the methodology and then also discuss Poisson Regression, Logistic Regression, Decision trees, Random Forests, K-NN classification, and unsupervised classification methods such as K-means clustering.
Throughout the course, the focus is on geospatial data and special considerations for spatial data such as spatial joins, map plotting, and dealing with spatial autocorrelation.
Important concepts including model selection, maximum likelihood estimation, differences between statistical inference and machine learning and more are explained conceptually in a manner intended for geospatial professionals rather than statisticians.
Check out the detailed breakdown of what’s inside the course
I have been programming and working with database applications for over 30 years, and specializing in geospatial applications for over 20 years. I am a believer in the 80/20 pareto principle which suggests that you only need to understand 20% of a subject in order to do 80% of your work. My goal in all my courses is to teach at the level of that 20% sweet spot and to provide my students with the background and the tools they need to learn the rest of what they need on their own.
Use your certificate to make a career change or to advance in your current career.
Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video Courses
Master prominent technologies at full length and become a valued certified professional.