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QGIS Python Programming Cookbook, Second Edition

You're reading from   QGIS Python Programming Cookbook, Second Edition Automating geospatial development

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787124837
Length 464 pages
Edition 2nd 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 (16) Chapters Close

QGIS Python Programming Cookbook - Second Edition
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Automating QGIS FREE CHAPTER 2. Querying Vector Data 3. Editing Vector Data 4. Using Raster Data 5. Creating Dynamic Maps 6. Composing Static Maps 7. Interacting with the User 8. QGIS Workflows 9. Other Tips and Tricks

Loading data from a spreadsheet


Spreadsheets are one of the most common methods used to collect and store simple geographic data. QGIS can work with text files called Comma Separated Value (CSV) files. Any spreadsheet can be converted to a CSV using the spreadsheet program. As long as the CSV data has a column representing x values, one column representing y values, and other columns representing data with the first row containing field names, QGIS can import it. Many organizations distribute geographic information as a CSV, so sooner or later, you will find yourself importing a CSV. Moreover, PyQGIS lets you do it programmatically. Note that a CSV can be delimited by any character as long as it is consistent. Also, the file extension of the CSV file doesn't matter as long as you specify the file type for QGIS.

Getting ready

We'll use a sample CSV file with point features representing points of interest in a region. You can download this sample from https://github.com/GeospatialPython/Learn...

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