Book Image

QGIS Python Programming Cookbook, Second Edition - Second Edition

By : Joel Lawhead
Book Image

QGIS Python Programming Cookbook, Second Edition - Second Edition

By: Joel Lawhead

Overview of this book

QGIS is a desktop geographic information system that facilitates data viewing, editing, and analysis. Paired with the most efficient scripting language—Python, we can write effective scripts that extend the core functionality of QGIS. Based on version QGIS 2.18, this book will teach you how to write Python code that works with spatial data to automate geoprocessing tasks in QGIS. It will cover topics such as querying and editing vector data and using raster data. You will also learn to create, edit, and optimize a vector layer for faster queries, reproject a vector layer, reduce the number of vertices in a vector layer without losing critical data, and convert a raster to a vector. Following this, you will work through recipes that will help you compose static maps, create heavily customized maps, and add specialized labels and annotations. As well as this, we’ll also share a few tips and tricks based on different aspects of QGIS.
Table of Contents (16 chapters)
QGIS Python Programming Cookbook - Second Edition
About the Author
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Joining a shapefile attribute table to a CSV file

Joining attribute tables to other database tables allows you to use a spatial data set to reference a dataset without any geometry, using a common key between the data tables. A very common use case for this is to join a vector dataset of census attributes to a more detailed census attribute dataset. That is the use case we will demonstrate here by linking a US census track file to a detailed Comma Separated Value (CSV) file containing more in-depth information.

Getting ready

For this recipe you will need a census tract shapefile and a CSV file containing the appropriate census data for the shapefile. You can download the sample dataset from the following URL:

Extract the data to a directory named /qgis_data/census.

How to do it...

The join operation is quite involved. We'll perform this operation and save the layer as a new shapefile with the joined attributes. Then, we'll load...