Download ArcPy and ArcGIS: Geospatial Analysis with Python by Silas Toms PDF

By Silas Toms

ISBN-10: 1783988665

ISBN-13: 9781783988662

Use the ArcPy module to automate the research and mapping of geospatial facts in ArcGIS

About This Book

  • Perform GIS research quicker by means of automating initiatives, similar to opting for info or buffering information, through having access to GIS instruments utilizing scripting
  • Access the spatial facts contained inside shapefiles and geodatabases, for updates, research or even transformation among spatial reference systems
  • Produce map books and automate the mapping of geospatial analyses, lowering the time had to produce and demonstrate the results

Who This publication Is For

If you're a GIS scholar or specialist who wishes an realizing of the way to take advantage of ArcPy to lessen repetitive initiatives and practice research speedier, this booklet is for you. it's also a necessary booklet for Python programmers who are looking to know how to automate geospatial analyses.

In Detail

ArcGIS makes it possible for complicated analyses of geographic details. The ArcPy module is used to script those ArcGIS analyses, supplying a effective technique to practice geo-analyses and to automate map production.

This ebook will advisor you from simple Python scripting to complicated ArcPy script instruments. This ebook begins with developing your Python setting, demonstrates a fancy ArcPy script instrument with a number of iterations, illustrates facts entry module cursors, and explains how one can use ArcPy Geometry sessions. Then, you'll find out how to output maps utilizing ArcPy.Mapping, and the way to create ArcGIS script tools.

With assistance from this ebook, it is possible for you to to create repeatable analyses decreasing the time-consuming nature of GIS, making you right into a GIS specialist as strong as a complete team.

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Extra resources for ArcPy and ArcGIS: Geospatial Analysis with Python

Example text

However, lots of existing scripts include import statements of this type so be aware of these consequences. The following are some best practices to use when naming variables. This is not required, and will not be used dogmatically in this book, but it can help organize the script and is helpful for others who will read these scripts. This improves the speed of writing a script, but it can be problematic in long scripts as the data type of a variable will not be obvious. Also, variables cannot start with a number.

If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea—let's do more of those! org/doc/humor/ for more information. The following are a number of important basic concepts, which will be used throughout this book and when crafting scripts for use with geospatial analyses. These modules can be part of the standard Python library of modules, such as the math module (used to do higher mathematical calculations) or, importantly, ArcPy, which will allow us to interact with ArcGIS.

Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one-- and preferably only one --obvious way to do Although that way may not be obvious at first unless you're Dutch. Now is better than never. Although never is often better than *right* now.

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