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Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python Understand GIS fundamentals and perform remote sensing data analysis using Python 3.7

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Product type Paperback
Published in Sep 2019
Publisher
ISBN-13 9781789959277
Length 456 pages
Edition 3rd Edition
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Table of Contents (15) Chapters Close

Preface 1. Section 1: The History and the Present of the Industry
2. Learning about Geospatial Analysis with Python FREE CHAPTER 3. Learning Geospatial Data 4. The Geospatial Technology Landscape 5. Section 2: Geospatial Analysis Concepts
6. Geospatial Python Toolbox 7. Python and Geographic Information Systems 8. Python and Remote Sensing 9. Python and Elevation Data 10. Section 3: Practical Geospatial Processing Techniques
11. Advanced Geospatial Python Modeling 12. Real-Time Data 13. Putting It All Together 14. Other Books You May Enjoy

OSMnx

The osmnx library combines Open Street Map (OSM) and the powerful NetworkX library to manage street networks used for routing. This library has dozens of dependencies which it rolls up to do all of the complex steps of downloading, analyzing, and visualizing street networks.

You can try to install osmnx using pip:

pip install osmnx

However, you may run into some installation issues due to the dependencies. In that case, it's easier to use the Conda system, which we'll introduce later in this chapter.

The following example uses osmnx to download street data from OSM for a city, creates a street network from it, and calculates some basic statistics:

>>> import osmnx as ox
>>> G = ox.graph_from_place('Bay Saint Louis, MS , USA', network_type='drive')
>>> stats = ox.basic_stats(G)
>>> stats["street_length_avg...
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