Book Image

Python for ArcGIS Pro

By : Silas Toms, Bill Parker
Book Image

Python for ArcGIS Pro

By: Silas Toms, Bill Parker

Overview of this book

Integrating Python into your day-to-day ArcGIS work is highly recommended when dealing with large amounts of geospatial data. Python for ArcGIS Pro aims to help you get your work done faster, with greater repeatability and higher confidence in your results. Starting from programming basics and building in complexity, two experienced ArcGIS professionals-turned-Python programmers teach you how to incorporate scripting at each step: automating the production of maps for print, managing data between ArcGIS Pro and ArcGIS Online, creating custom script tools for sharing, and then running data analysis and visualization on top of the ArcGIS geospatial library, all using Python. You’ll use ArcGIS Pro Notebooks to explore and analyze geospatial data, and write data engineering scripts to manage ongoing data processing and data transfers. This exercise-based book also includes three rich real-world case studies, giving you an opportunity to apply and extend the concepts you studied earlier. Irrespective of your expertise level with Esri software or the Python language, you’ll benefit from this book’s hands-on approach, which takes you through the major uses of Python for ArcGIS Pro to boost your ArcGIS productivity.
Table of Contents (20 chapters)
1
Part I: Introduction to Python Modules for ArcGIS Pro
5
Part II: Applying Python Modules to Common GIS Tasks
10
Part III: Geospatial Data Analysis
14
Part IV: Case Studies
18
Other Books You May Enjoy
19
Index

Introduction to Pandas

Pandas is a Python module used for data analysis and manipulation. It is an open-source module that can be installed and used separately from ArcGIS Pro; in fact, it is the most popular Python data analysis module. As it is so useful and well-known, it is included along with Python when ArcGIS Pro is installed.

Its origins lie in the financial world, where statistical analysis is used constantly. In 2007, needing a more powerful tool to perform quantitative analysis, a financial analyst and programmer named Wes McKinney developed the first version of Pandas. It was made open source in 2012 and was quickly recognized as a powerful and flexible data tool.

Pandas DataFrames

The basic data structure in Pandas is the Pandas DataFrame. A Pandas DataFrame is essentially a data table, much like ArcGIS attribute tables or Excel tables, but with a whole lot of built-in features that make it easy to manipulate and manage data.

Pandas Series

DataFrames...