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Geospatial Development By Example with Python

You're reading from   Geospatial Development By Example with Python Build your first interactive map and build location-aware applications using cutting-edge examples in Python

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781785282355
Length 340 pages
Edition 1st Edition
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Author (1):
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Pablo Carreira Pablo Carreira
Author Profile Icon Pablo Carreira
Pablo Carreira
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Table of Contents (12) Chapters Close

Preface 1. Preparing the Work Environment 2. The Geocaching App FREE CHAPTER 3. Combining Multiple Data Sources 4. Improving the App Search Capabilities 5. Making Maps 6. Working with Remote Sensing Images 7. Extract Information from Raster Data 8. Data Miner App 9. Processing Big Images 10. Parallel Processing Index

Searching for data and crossing information


Now that we have our database populated with some data, it's time to get some information from it; let's explore what kind of information all those POIs hold. We know that we downloaded points that contain at least one of the amenity or store keys.

Amenities are described by OSM as any type of community facilities. As an exercise, let's see a list of amenity types that we got from the points:

  1. Edit your geodata_app.py file's if __name__ == '__main__': block:

    if __name__ == '__main__':
        amenity_values = Tag.objects.filter(
            key='amenity').distinct('value').values_list('value')
        for item in amenity_values:
            print(item[0])

    Here we take the Tag model, access its manager (objects), then filter the tags whose key='amenity'. Then we separate only distinct values (exclude repeated values from the query). The final part—values_list('value')—tells Django that we don't want it to create Tag models, we only want a list of values.

  2. Run the code...

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