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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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Toc

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

dbfpy

Both OGR and PyShp read and write the .dbf files because they are part of the shapefile specification. The .dbf files contain the attributes and fields for the shapefiles. However, both libraries have very basic .dbf support. Occasionally, you will need to do some heavy-duty DBF work. The dbfpy3 module is a pure Python module dedicated to working with .dbf files. It is currently hosted on GitHub. You can force easy_install to find the download by specifying the download file:

easy_install -f
https://github.com/GeospatialPython/dbfpy3/archive/master.zip

If you are using pip to install packages, use the following command:

pip install
https://github.com/GeospatialPython/dbfpy3/archive/master.zip

The following shapefile has over 600 .dbf records representing US Census Bureau tracts, which make it a good sample for trying out dbfpy: https://github.com/GeospatialPython/Learn/raw...

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