Unlocking the Power of Python for Geospatial Analysis with GeoPandas and Folium

A comprehensive guide on how to use these libraries for mapping and analyzing geographical data

Photo by Kyle Glenn on Unsplash

In today’s world, location-based information is becoming increasingly important. Whether you are an urban planner, environmental scientist or simply interested in visualizing your travel history, geospatial analysis can help uncover valuable insights from spatial datasets.

This article aims to introduce two powerful open source tools — GeoPandas and Folium which make working with geospatial data in Python easier than ever before.

Part I: Getting Started with GeoPandas

What is GeoPandas?

GeoPandas is a Python library used for manipulating and analyzing geospatial data. It combines the capabilities of pandas, a popular library for data manipulation, with those of shapely, a library for handling geometric objects such as points, lines, and polygons.

By doing so, it allows users to perform complex operations on spatial data using familiar Pandas functions like merge(), join() etc., while also providing methods specific to geographic features.

Installing GeoPandas