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QGIS Python Programming Cookbook, Second Edition
QGIS Python Programming Cookbook, Second Edition

QGIS Python Programming Cookbook, Second Edition: Automating geospatial development , Second Edition

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QGIS Python Programming Cookbook, Second Edition

Chapter 2. Querying Vector Data

In this chapter, we will cover the following recipes:

  • Loading a vector layer from a file sample
  • Loading a vector layer from a geodatabase
  • Examining vector layer features
  • Examining vector layer attributes
  • Filtering a layer by geometry
  • Filtering a layer by attributes
  • Buffering a feature
  • Measuring the distance between two points
  • Measuring distance along a line
  • Calculating the area of a polygon
  • Creating a spatial index
  • Calculating the bearing of a line
  • Loading data from a spreadsheet
  • Accessing layer metadata

Introduction

This chapter demonstrates how to work with vector data through Python in QGIS. We will first work through loading different sources of vector data. Next, we'll move on to examining the contents of the data. Then, we'll spend the remainder of the chapter performing spatial and database operations on vector data.

Loading a vector layer from a file sample

Vector data stored in a local file is one of the most common geospatial data formats. Vector data typically stores geometry with associated attributes. In this recipe, we'll load a vector data file, in this case a shapefile, as a vector layer in QGIS.

Getting ready

For ease of following the examples in this book, it is recommended that you create a directory called qgis_data in your root or user directory,which will provide a short pathname. This setup will help prevent the occurrence of any frustrating errors resulting from path-related issues on a given system. In this recipe, and others, we'll use a point shapefile of the New York City museums, which you can download from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip this file and place the shapefile's contents in a directory named nyc within your qgis_data directory.

How to do it...

Now, we'll walk through the steps of loading a shapefile...

Loading a vector layer from a geodatabase

The PostGIS geodatabase is based on the open source Postgres database. The geodatabase provides powerful geospatial data management and operations. PyQGIS fully supports PostGIS as a data source. In this recipe, we'll add a layer from a PostGIS database.

Getting ready

Installing and configuring PostGIS is beyond the scope of this book, so we'll use a sample geospatial database interface from the excellent service http://www.qgiscloud.com/. It has its own Python plugin called QGIS Cloud. You can sign up for free and create your own geodatabase online by following the site's instructions, or you can use the example used in this recipe.

How to do it...

Perform the following steps to load a PostGIS layer into a QGIS map:

  1. First, create a new DataSourceURI instance:
            uri = QgsDataSourceURI() 
    
  2. Next, create the database connection string:
            uri.setConnection("spacialdb.com", "9999", "lzmjzm_hwpqlf&quot...

Examining vector layer features

Once a vector layer is loaded, you may want to investigate the data. In this recipe, we'll load a vector point layer from a shapefile and take a look at the and y coordinates of the first point.

Getting ready

We'll use the same New York City Museums layer from the Loading a vector layer from a file recipe of this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will load the layer, get the features, grab the first feature, obtain its geometry, and take a look at the values for the first point:

  1. First, load the layer:
            layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                                   "New York City Museums", "ogr") 
    
  2. Next...

Examining vector layer attributes

A true GIS layer contains both spatial geometry and non-spatial attributes. In this recipe, we'll access a vector point layer's attributes in PyQGIS. We'll use a file-based layer from a shapefile, but once a layer is loaded in QGIS, every vector layer works the same way.

Getting ready

Once again, we'll use the same New York City Museums layer from the Loading a vector layer from a file recipe in this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In the following steps, we'll load the layer, access the features iterator, grab the first feature, and then view the attributes as a Python list:

  1. First, load the shapefile as a vector layer:
            layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp...

Introduction


This chapter demonstrates how to work with vector data through Python in QGIS. We will first work through loading different sources of vector data. Next, we'll move on to examining the contents of the data. Then, we'll spend the remainder of the chapter performing spatial and database operations on vector data.

Loading a vector layer from a file sample


Vector data stored in a local file is one of the most common geospatial data formats. Vector data typically stores geometry with associated attributes. In this recipe, we'll load a vector data file, in this case a shapefile, as a vector layer in QGIS.

Getting ready

For ease of following the examples in this book, it is recommended that you create a directory called qgis_data in your root or user directory,which will provide a short pathname. This setup will help prevent the occurrence of any frustrating errors resulting from path-related issues on a given system. In this recipe, and others, we'll use a point shapefile of the New York City museums, which you can download from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip this file and place the shapefile's contents in a directory named nyc within your qgis_data directory.

How to do it...

Now, we'll walk through the steps of loading a shapefile and adding it to the map...

Loading a vector layer from a geodatabase


The PostGIS geodatabase is based on the open source Postgres database. The geodatabase provides powerful geospatial data management and operations. PyQGIS fully supports PostGIS as a data source. In this recipe, we'll add a layer from a PostGIS database.

Getting ready

Installing and configuring PostGIS is beyond the scope of this book, so we'll use a sample geospatial database interface from the excellent service http://www.qgiscloud.com/. It has its own Python plugin called QGIS Cloud. You can sign up for free and create your own geodatabase online by following the site's instructions, or you can use the example used in this recipe.

How to do it...

Perform the following steps to load a PostGIS layer into a QGIS map:

  1. First, create a new DataSourceURI instance:

            uri = QgsDataSourceURI() 
    
  2. Next, create the database connection string:

            uri.setConnection("spacialdb.com", "9999", "lzmjzm_hwpqlf",
                              "lzmjzm_hwpqlf...

Examining vector layer features


Once a vector layer is loaded, you may want to investigate the data. In this recipe, we'll load a vector point layer from a shapefile and take a look at the and y coordinates of the first point.

Getting ready

We'll use the same New York City Museums layer from the Loading a vector layer from a file recipe of this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will load the layer, get the features, grab the first feature, obtain its geometry, and take a look at the values for the first point:

  1. First, load the layer:

            layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                                   "New York City Museums", "ogr") 
    
  2. Next, get an iterator of the layer's features:

            features ...

Examining vector layer attributes


A true GIS layer contains both spatial geometry and non-spatial attributes. In this recipe, we'll access a vector point layer's attributes in PyQGIS. We'll use a file-based layer from a shapefile, but once a layer is loaded in QGIS, every vector layer works the same way.

Getting ready

Once again, we'll use the same New York City Museums layer from the Loading a vector layer from a file recipe in this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In the following steps, we'll load the layer, access the features iterator, grab the first feature, and then view the attributes as a Python list:

  1. First, load the shapefile as a vector layer:

            layer = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                                ...

Filtering a layer by geometry


In this recipe, we'll perform a spatial operation to select the subset of a point layer based on the points contained in an overlapping polygon layer. We'll use shapefiles in both the cases, with one being a point layer and the other a polygon. This kind of subset is one of the most common GIS operations.

Getting ready

We will need two new shapefiles that have not been used in the previous recipes. You can download the point layer from https://github.com/GeospatialPython/Learn/raw/master/MSCities_Geo_Pts.zip.

Similarly, you can download the geometry layer from https://github.com/GeospatialPython/Learn/raw/master/GIS_CensusTract.zip.

Unzip these shapefiles and place them in a directory named ms within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we will perform several steps to select features in the point layer that fall within the polygon layer, as follows:

  1. First, load the point layer:

            lyrPts = QgsVectorLayer...

Filtering a layer by attributes


In addition to the spatial queries outlined in the previous recipe, we can also subset a layer by its attributes. This type of query resembles a more traditional relational database query and, in fact, uses SQL statements. In this recipe, we will filter a point shapefile-based layer by an attribute.

Getting ready

We'll use the same New York City Museums layer used in the previous recipes in this chapter. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In this recipe, we'll filter the layer by an attribute, select the filtered features, and zoom to them, as follows:

  1. First, we load the point layer:

            lyrPts = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                                    "Museums", "ogr") 
    
  2. Next, we add the layer...

Buffering a feature


Buffering a feature creates a polygon around a feature as a selection geometry or just a simple visualization. In this recipe, we'll buffer a point in a point feature and add the returned polygon geometry to the map.

Getting ready

Once again, we'll use the same New York City Museums layer. You can download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

This recipe involves both a spatial operation and multiple visualizations. To do this, perform the following steps:

  1. First, load the layer:

            lyr = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                  "Museums", "ogr") 
    
  2. Next, visualize the layer on the map:

            QgsMapLayerRegistry.instance().addMapLayers([lyr]) 
    
  3. Access the layer's features:

            fts = lyr.getFeatures() 
    
  4. Grab the first...

Measuring the distance between two points


In the QgsDistanceArea object, PyQGIS has excellent capabilities for measuring the distance. We'll use this object for several recipes, starting with measuring the distance between two points.

Getting ready

If you don't already have the New York City Museums layer used in the previous recipes in this chapter, download the layer from https://github.com/GeospatialPython/Learn/raw/master/NYC_MUSEUMS_GEO.zip.

Unzip that file and place the shapefile's contents in a directory named nyc within your qgis_data directory, within your root or home directory.

How to do it...

In the following steps, we'll extract the first and last points in the layer's point order and measure the distance between them:

  1. First, import the library that contains the QGIS contents:

            from qgis.core import QGis 
    
  2. Then, load the layer:

            lyr = QgsVectorLayer("/qgis_data/nyc/NYC_MUSEUMS_GEO.shp",
                                 "Museums", "ogr") 
    
  3. Access the features:

    ...

Measuring distance along a line


In this recipe, we'll measure the distance along a line with multiple vertices.

Getting ready

For this recipe, we'll use a line shapefile with two features. You can download the shapefile as a .zip file from https://github.com/GeospatialPython/Learn/raw/master/paths.zip.

Unzip the shapefile into a directory named qgis_data/shapes within your root or home directory.

How to do it...

The steps for this recipe are fairly straightforward. We'll extract the geometry from the first line feature and pass it to the measurement object, as shown here:

  1. First, we must load the QGIS constants library:

            from qgis.core import QGis 
    
  2. Load the line layer:

            lyr = QgsVectorLayer("/qgis_data/shapes/paths.shp", "Route", "ogr") 
    
  3. Grab the features:

            fts = lyr.getFeatures() 
    
  4. Get the first feature:

            route = fts.next() 
    
  5. Create the measurement object instance:

            d = QgsDistanceArea() 
    
  6. Then, we must configure the QgsDistanceArea object to...

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Key benefits

  • Delve into the undocumented features of the QGIS API
  • Get a set of user-friendly recipes that can automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes
  • This book has a complete code upgrade to QGIS 2.18 and 30 new, valuable recipes

Description

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.

Who is this book for?

This book is for geospatial analysts who want to learn more about automating everyday GIS tasks as well as programmers responsible for building GIS applications. The short, reusable recipes make concepts easy to understand and combine so you can build larger applications that are easy to maintain.

What you will learn

  • Use Python and QGIS to produce captivating GIS visualizations and build complex map layouts
  • Find out how to effectively use the poorly-documented and undocumented features of the QGIS Python API
  • Automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes
  • Create, import, and edit geospatial data on disk or in-memory
  • Change QGIS settings programmatically to control default behavior
  • Automatically generate PDF map books
  • Build dynamic forms for field input
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Table of Contents

9 Chapters
1. Automating QGIS Chevron down icon Chevron up icon
2. Querying Vector Data Chevron down icon Chevron up icon
3. Editing Vector Data Chevron down icon Chevron up icon
4. Using Raster Data Chevron down icon Chevron up icon
5. Creating Dynamic Maps Chevron down icon Chevron up icon
6. Composing Static Maps Chevron down icon Chevron up icon
7. Interacting with the User Chevron down icon Chevron up icon
8. QGIS Workflows Chevron down icon Chevron up icon
9. Other Tips and Tricks Chevron down icon Chevron up icon

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Leo Jul 30, 2017
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The book is good, some small bugs but doesn't really affect reading and learning. However the bad thing is I find the same book on Packt website and it is only $10 with a more programmer friendly interface... I cannot even copy and test the code in kindle reader...
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宮崎 知与 Oct 02, 2021
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バージョンが古く活用しすらいので、残念❗
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  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela