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Learning Geospatial Analysis with Python-Second Edition

You're reading from   Learning Geospatial Analysis with Python-Second Edition An effective guide to geographic information systems and remote sensing analysis using Python 3

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Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 pages
Edition 1st Edition
Languages
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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 (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python FREE CHAPTER 2. Geospatial Data 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modeling 9. Real-Time Data 10. Putting It All Together Index

Using spreadsheets


Spreadsheets such as Microsoft Office Excel and Open Office Calc are inexpensive (even free), ubiquitous, easy to use, and great for recording structured data. For these reasons, spreadsheets are widely used to collect data for entry into a GIS format. As an analyst, you will find yourself working with spreadsheets frequently. In the previous chapters, we discussed the CSV format, which is a text file with the same basic rows and columns data structure as a spreadsheet. For CSV files, you use Python's built-in csv module. But most of the time, people don't bother exporting a true spreadsheet to a generic CSV file. That's where the pure Python xlrd module comes into play. The name xlrd is short for Excel Reader and is available from PyPI with its accompanying xlwt (Excel Writer) module. These two modules make reading and writing Excel spreadsheets a snap. Combine it with PyShp and you can move back and forth between spreadsheets and shapefiles with ease.

This example demonstrates...

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