After installation, open Pycharm, and you will be prompted to create your first project:
Click on create new project and then choose
c:\geopyas your project location. In Linux, you can put the project inside your home folder—for example,/home/myname/geopy. Click on Create to create the project.
In Windows, you will receive a security alert; this is Pycharm trying to access the Internet. It's recommended that you allow it so that you can later check for updates or download plugins:
Finally, you should see the following window on your project workspace. Take some time to explore the menus and buttons, try right-clicking on your project folder to see the options:
Geospatial Development By Example with Python
By :
Geospatial Development By Example with Python
By:
Overview of this book
From Python programming good practices to the advanced use of analysis packages, this book teaches you how to write applications that will perform complex geoprocessing tasks that can be replicated and reused.
Much more than simple scripts, you will write functions to import data, create Python classes that represent your features, and learn how to combine and filter them.
With pluggable mechanisms, you will learn how to visualize data and the results of analysis in beautiful maps that can be batch-generated and embedded into documents or web pages.
Finally, you will learn how to consume and process an enormous amount of data very efficiently by using advanced tools and modern computers’ parallel processing capabilities.
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Geospatial Development By Example with Python
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Table of Contents (17 chapters)
Geospatial Development By Example with Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Preparing the Work Environment
The Geocaching App
Combining Multiple Data Sources
Improving the App Search Capabilities
Making Maps
Working with Remote Sensing Images
Extract Information from Raster Data
Data Miner App
Processing Big Images
Parallel Processing
Index
Customer Reviews