Python For ArcGIS

1. Working with HTML and KML

   • Laura Tateosian

   Pages 385-413

2. Classes

   • Laura Tateosian

   Pages 415-434

3. User Interfaces for File and Folder Selection

   • Laura Tateosian

   Pages 435-448

4. ArcGIS Python GUIs

   • Laura Tateosian

   Pages 449-504

5. Mapping Module

   • Laura Tateosian

   Pages 505-530

6. Back Matter

   Pages 531-538

   PDF

This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. It builds essential programming skills for automating GIS analysis. Over 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. Readers will learn to: • Write and run Python in the ArcGIS Python Window, the PythonWin IDE, and the PyScripter IDE • Work with Python syntax and data types • Call ArcToolbox tools, batch process GIS datasets, and manipulate map documents using the arcpy package • Read and modify proprietary and ASCII text GIS data • Parse HTML web pages and KML datasets • Create Web pages and fetch GIS data from Web sources. • Build user-interfaces with the native Python file dialog toolkit or the ArcGIS Script tools and PyToolboxes Python for ArcGIS is designed as a primary textbook for advanced-level students in GIS. Researchers, government specialists and professionals working in GIS will also find this book useful asa reference.

• ArcGIS
• ArcPy
• Batch processing
• Computer programming
• GIS
• Geographic information science
• Geoprocessing
• Geospatial analysis
• Geospatial data processing
• Geospatial information science
• Python
• Scripting
• Streamline workflow

• North Carolina State University, Raleigh, USA

  Laura Tateosian

Laura G. Tateosian is a professor at the Center for Geospatial Analytics at North Carolina State University. She earned her B.A. in Mathematics from Towson University, her M.S. in Mathematics from the University of Oklahoma, and her Ph.D. in computer science from North Carolina State University. She has more than 8 years of experience teaching Python programming for GIS and receives outstanding teaching evaluations. In 2014, she received an award for her teaching at North Carolina State University. Her research involves geospatial data analysis, aesthetic geovisualization, eye-tracking for map and visualization design, and automatic narrative mapping with Python and ArcGIS. Her research has published in refereed conferences and journals, such as, Information Visualization, International Journal for Uncertainty Quantification, Transactions in GIS, ACM Transactions on Graphics, IEEE Transactions on Visualization and Computer Graphics, the proceedings of the International Symposium on Non-Photorealistic Animation and Rendering, the International Symposium on Applied Perception in Graphics and Visualization, and IEEE Computer Graphics & Applications (Visualization Viewpoints).

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