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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 FREE CHAPTER
2. Learning about Geospatial Analysis with Python 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

ZIP and TAR files

Geospatial datasets often consist of multiple files. For this reason, they are often distributed as ZIP or TAR file archives. These formats can also compress data, but their ability to bundle multiple files is the primary reason they are used for geospatial data. While the TAR format doesn't contain a compression algorithm, it incorporates gzip compression and offers it as a program option. Python has standard modules for reading and writing both ZIP and TAR archives. These modules are called zipfile and tarfile, respectively.

The following example extracts the hancock.shp, hancock.shx, and hancock.dbf files contained in the hancock.zip file we downloaded using urllib for use in the previous examples. This example assumes that the ZIP file is in the current directory:

>>> import zipfile
>>> zip = open("hancock.zip", "rb&quot...
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