Geoprocessing with Python

Chapter 5. Filtering data with OGR

This chapter covers

• Efficiently selecting features using attribute values
• Using spatial location to select features
• Joining attribute tables from different layers

Back in chapter 3, you learned how to iterate through all of the features in a layer and use attribute values for each one to determine if it was interesting. You’ve got easier ways to throw out features that you don’t want, however, and that’s where filters come in. With filters you can easily select features that match specific criteria, such as all animal GPS locations from a certain day or all crabapple trees from a city tree inventory. Filters also let you limit features by spatial extent, so you could limit your crabapple trees to a specific ...