Chapter 2. Data Management

In this chapter, we will cover the following recipes:

Joining layer data
Cleaning up the attribute table
Configuring relations
Joining tables in databases
Creating views in SpatiaLite
Creating views in PostGIS
Creating spatial indexes
Georeferencing rasters
Georeferencing vector layers
Creating raster overviews (pyramids)
Building virtual rasters (catalogs)

Introduction

One of the reasons to use QGIS is its many features that enable management and analysis preparation of spatial data in a visual manner. This chapter focuses on common operations that users need to perform to get data ready for other uses, such as analysis, cartography, or input into other programs.

In this chapter, you will find recipes to manage vector as well as raster data. These recipes cover the handling of data from both file and database sources.

Joining layer data

We often get data in different formats and information spread over multiple files. Therefore, one important skill to know is how to join attribute data from different layers. Joining data is a way to combine data from multiple tables based on common values, such as IDs or categories.

This exercise shows you how to use the join functionality in Layer Properties to join geographic census tract data to tabular population data and how to save the results to a new file.

Getting ready

To follow this exercise, load the census tracts in census_wake2000.shp using Add Vector Layer (you can also drag and drop the shapefile from the file browser to QGIS) and population data in census_wake2000_pop.csv using Add Delimited Text Layer.

Tip

You can also load the .csv text file using Add Vector Layer, but this will load all data as text columns because the .csv file does not come with a .csvt file to specify data types. Instead, the Add Delimited Text Layer tool will scan the data and determine...

Cleaning up the attribute table

There are many reasons why we need to clean up attribute tables every now and then. These may be because we receive badly structured or named data from external sources, or because data processing, such as the layer joins that we performed in the previous exercise, require some post processing. This recipe shows us how to use attribute table and the Table Manager plugin to rename, delete, and reorder columns, as well as how to convert between different data types using Field Calculator.

Getting ready

If you performed the previous recipe, just save the joined layer to a new shapefile; otherwise, load census_wake2000_pop.shp. In any case, you will notice that the dataset contains a lot of duplicate information, and the column names could use some love as well. To follow this recipe, you should also install and enable the Table Manager plugin by navigating to Plugins | Manage and Install Plugins.

How to do it…

Our first step to clean up this dataset is to...

Configuring relations

In the Joining layer data recipe, we discussed that joins only append additional columns to existing features (1:1 or n:1 relationships). Using joins, it is, therefore, not possible to model 1:n relationships, such as "one zip code area containing n schools". These kinds of relationships can instead be modeled using relations. This recipe introduces the concept of relations and shows how you can put them to use.

Getting ready

To follow this exercise, load zip code areas and schools from zipcodes_wake.shp and schools_wake.shp.

How to do it…

Relations are configured in Project Properties. The dialog is very similar to the join dialog:

Define the two layers (Referencing/Child and Referenced/Parent), as well as the fields containing the common values/IDs. As you want to model "one zip code area contains n schools," the zip code dataset is the parent layer and the school dataset is the child layer. The connection between both datasets is established...

Joining tables in databases

If you use a database (SpatiaLite or PostGIS) to store your data, vector and nonspatial, then you also have the option of using the database and SQL to perform tables joins. The primary advantages of this method include being able to filter data before loading in the map, perform multitable joins (three or more), and have full control over the details of the join via queries.

Getting ready

You'll need at least two layers in either a SpatiaLite or PostGIS database. These two layers need at least one column in common, and the column in common should contain unique values in at least one table. In this case, our example uses the census_wake_2000 polygon layer and census_wake_2000_pop.csv.

How to do it…

Open the DB Manager plugin that comes with QGIS. You can find this in the Database menu.
Select your database from the tree on the left-hand side, use cookbook.db in SpatiaLite (which was created in Chapter 1, Data Input and Output).
Tip
If you don't see...

Creating views in SpatiaLite

In a database, view is a stored query. Every time you open it, the query is run and fresh results are generated. To use views as layers in QGIS takes a couple of steps.

Getting ready

For this recipe, you'll need a query that returns results containing a geometry. The example that we'll use is the query from the Joining tables in databases recipe (the previous recipe) where attributes were joined 1:1 between the census polygons and the population CSV. The QSpatiaLite plugin is recommended for this recipe.

How to do it…

The GUI method is described as follows:

Using the QspatiaLite plugin (which is in the Database menu, if you've activated it) place the following in the query:
```
SELECT *
FROM census_wake2000 as a
JOIN census_wake2000_pop as b
ON a.stfid = b.stfid;
```
From the Option dropdown, select the last choice, Create Spatial View & Load in QGIS, and set the Geometry field box value to the name of your geometry field from your spatial layer....

Introduction

One of the reasons to use QGIS is its many features that enable management and analysis preparation of spatial data in a visual manner. This chapter focuses on common operations that users need to perform to get data ready for other uses, such as analysis, cartography, or input into other programs.

In this chapter, you will find recipes to manage vector as well as raster data. These recipes cover the handling of data from both file and database sources.

Joining layer data

We often get data in different formats and information spread over multiple files. Therefore, one important skill to know is how to join attribute data from different layers. Joining data is a way to combine data from multiple tables based on common values, such as IDs or categories.

This exercise shows you how to use the join functionality in Layer Properties to join geographic census tract data to tabular population data and how to save the results to a new file.

Getting ready

To follow this exercise, load the census tracts in census_wake2000.shp using Add Vector Layer (you can also drag and drop the shapefile from the file browser to QGIS) and population data in census_wake2000_pop.csv using Add Delimited Text Layer.

Tip

You can also load the .csv text file using Add Vector Layer, but this will load all data as text columns because the .csv file does not come with a .csvt file to specify data types. Instead, the Add Delimited Text Layer tool will scan the data and determine...

Cleaning up the attribute table

There are many reasons why we need to clean up attribute tables every now and then. These may be because we receive badly structured or named data from external sources, or because data processing, such as the layer joins that we performed in the previous exercise, require some post processing. This recipe shows us how to use attribute table and the Table Manager plugin to rename, delete, and reorder columns, as well as how to convert between different data types using Field Calculator.

Getting ready

If you performed the previous recipe, just save the joined layer to a new shapefile; otherwise, load census_wake2000_pop.shp. In any case, you will notice that the dataset contains a lot of duplicate information, and the column names could use some love as well. To follow this recipe, you should also install and enable the Table Manager plugin by navigating to Plugins | Manage and Install Plugins.

How to do it…

Our first step to clean up this dataset is to delete...

Configuring relations

In the Joining layer data recipe, we discussed that joins only append additional columns to existing features (1:1 or n:1 relationships). Using joins, it is, therefore, not possible to model 1:n relationships, such as "one zip code area containing n schools". These kinds of relationships can instead be modeled using relations. This recipe introduces the concept of relations and shows how you can put them to use.

Getting ready

To follow this exercise, load zip code areas and schools from zipcodes_wake.shp and schools_wake.shp.

How to do it…

Relations are configured in Project Properties. The dialog is very similar to the join dialog:

Define the two layers (Referencing/Child and Referenced/Parent), as well as the fields containing the common values/IDs. As you want to model "one zip code area contains n schools," the zip code dataset is the parent layer and the school dataset is the child layer. The connection between both datasets is established based on the zip code fields...

Joining tables in databases

If you use a database (SpatiaLite or PostGIS) to store your data, vector and nonspatial, then you also have the option of using the database and SQL to perform tables joins. The primary advantages of this method include being able to filter data before loading in the map, perform multitable joins (three or more), and have full control over the details of the join via queries.

Getting ready

You'll need at least two layers in either a SpatiaLite or PostGIS database. These two layers need at least one column in common, and the column in common should contain unique values in at least one table. In this case, our example uses the census_wake_2000 polygon layer and census_wake_2000_pop.csv.

How to do it…

Open the DB Manager plugin that comes with QGIS. You can find this in the Database menu.
Select your database from the tree on the left-hand side, use cookbook.db in SpatiaLite (which was created in Chapter 1, Data Input and Output).
Tip
If you don't see this database listed...

Creating views in SpatiaLite

In a database, view is a stored query. Every time you open it, the query is run and fresh results are generated. To use views as layers in QGIS takes a couple of steps.

Getting ready

For this recipe, you'll need a query that returns results containing a geometry. The example that we'll use is the query from the Joining tables in databases recipe (the previous recipe) where attributes were joined 1:1 between the census polygons and the population CSV. The QSpatiaLite plugin is recommended for this recipe.

How to do it…

The GUI method is described as follows:

Using the QspatiaLite plugin (which is in the Database menu, if you've activated it) place the following in the query:
```
SELECT *
FROM census_wake2000 as a
JOIN census_wake2000_pop as b
ON a.stfid = b.stfid;
```
From the Option dropdown, select the last choice, Create Spatial View & Load in QGIS, and set the Geometry field box value to the name of your geometry field from your spatial layer. In this example, this is...

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