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Using GeoPandas for Geospatial Analysis in Python

Vectorial Data

Explore the core vectorial data types used in GIS such as points, lines, and polygons along with their multi-part counterparts. Understand why multi geometries are necessary for complex shapes like the USA map. Discover common GIS vector data formats including Shapefiles, GeoJSON, KML, and GeoPackage, and see examples of how these formats represent spatial data. This lesson will help you recognize and work with different vector data types and file formats using GeoPandas in Python.

We'll cover the following...

Vectorial data types

In this lesson, we'll take a deeper look into vectorial data types and the main file formats used in the GIS domain.

The three basic classes of vectorial geometric objects supported by GeoPandas are:

  • Point and MultiPoints

  • Line and MultiLines

  • Polygon and MultiPolygons

Basic classes of vectorial geometric objects
Basic classes of vectorial geometric objects

But why does every data type previously mentioned appear in the bullet points with its collection counterpart (e.g., Point and MultiPoints)? To understand this, imagine that we're trying to represent a single American state as vectorial data. Take Colorado, for example—it has a simple, almost squared, shape. It can be easily defined by a collection of coordinates where the last one repeats the first to represent a closed polygon, as shown below.

The Colorado state polygon defined by a collection of coordinates
The Colorado state polygon defined by a collection of coordinates

On the other ...