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

Working with legend and text elements in the layout

Now that you have all of your layers on your map, you need to make sure those layers are properly called out in your legend. In this section, you will take layers you just added to the map and add them to your legend. They will be added using the default legend style you set above in the Legend Item elements section.

In addition, you also want to add some details about each highlighted block group. Your map would be much more useful to readers if you included a table that contained the percentage of each race group in the highlighted block group on your map. This will allow them not only to see the race groups in the dot density map but also to reference the percentage each occupies in the block group.

You will do this by creating a list and data dictionary that will be used to extract data from the attribute table of the AlamedaContraCostaCounty_RaceHispanic_BlockGroup. This data will be extracted in the next section to...