Python Geospatial Analysis Cookbook
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Python Geospatial Analysis Cookbook
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Author : Michael Diener
language : en
Publisher:
Release Date : 2015
Python Geospatial Analysis Cookbook written by Michael Diener and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Geographic information systems categories.
Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with PythonAbout This Book* Explore the practical process of using geospatial analysis to solve simple to complex problems with reusable recipes* Concise step-by-step instructions to teach you about projections, vector, raster, overlay, indoor routing and topology analysis* Create a basic indoor routing application with geodjangoWho This Book Is ForIf you are a student, teacher, programmer, geospatial or IT administrator, GIS analyst, researcher, or scientist looking to do spatial analysis, then this book is for you. Anyone trying to answer simple to complex spatial analysis questions will get a working demonstration of the power of Python with real-world data. Some of you may be beginners with GIS, but most of you will probably have a basic understanding of geospatial analysis and programming.What You Will Learn* Discover the projection and coordinate system information of your data and learn how to transform that data into different projections* Import or export your data into different data formats to prepare it for your application or spatial analysis* Use the power of PostGIS with Python to take advantage of the powerful analysis functions* Execute spatial analysis functions on vector data including clipping, spatial joins, measuring distances, areas, and combining data to new results* Create your own set of topology rules to perform and ensure quality assurance rules in Python* Find the shortest indoor path with network analysis functions in easy, extensible recipes revolving around all kinds of network analysis problems* Visualize your data on a map using the visualization tools and methods available to create visually stunning results* Build an indoor routing web application with GeoDjango to include your spatial analysis tools built from the previous recipesIn DetailGeospatial development links your data to places on the Earth's surface. Its analysis is used in almost every industry to answer location type questions. Combined with the power of the Python programming language, which is becoming the de facto spatial scripting choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems.This book begins by tackling the installation of the necessary software dependencies and libraries needed to perform spatial analysis with Python. From there, the next logical step is to prepare our data for analysis; we will do this by building up our tool box to deal with data preparation, transformations, and projections. Now that our data is ready for analysis, we will tackle the most common analysis methods for vector and raster data. To check or validate our results, we will explore how to use topology checks to ensure top-quality results. This is followed with network routing analysis focused on constructing indoor routes within buildings, over different levels.Finally, we put several recipes together in a GeoDjango web application that demonstrates a working indoor routing spatial analysis application. The round trip will provide you all the pieces you need to accomplish your own spatial analysis application to suit your requirements.Style and approachEasy-to-follow, step-by-step recipes, explaining from start to finish how to accomplish real-world tasks.
Python Geospatial Analysis Cookbook
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Author : Michael Diener
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-11-30
Python Geospatial Analysis Cookbook written by Michael Diener and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-30 with Computers categories.
Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python About This Book Explore the practical process of using geospatial analysis to solve simple to complex problems with reusable recipes Concise step-by-step instructions to teach you about projections, vector, raster, overlay, indoor routing and topology analysis Create a basic indoor routing application with geodjango Who This Book Is For If you are a student, teacher, programmer, geospatial or IT administrator, GIS analyst, researcher, or scientist looking to do spatial analysis, then this book is for you. Anyone trying to answer simple to complex spatial analysis questions will get a working demonstration of the power of Python with real-world data. Some of you may be beginners with GIS, but most of you will probably have a basic understanding of geospatial analysis and programming. What You Will Learn Discover the projection and coordinate system information of your data and learn how to transform that data into different projections Import or export your data into different data formats to prepare it for your application or spatial analysis Use the power of PostGIS with Python to take advantage of the powerful analysis functions Execute spatial analysis functions on vector data including clipping, spatial joins, measuring distances, areas, and combining data to new results Create your own set of topology rules to perform and ensure quality assurance rules in Python Find the shortest indoor path with network analysis functions in easy, extensible recipes revolving around all kinds of network analysis problems Visualize your data on a map using the visualization tools and methods available to create visually stunning results Build an indoor routing web application with GeoDjango to include your spatial analysis tools built from the previous recipes In Detail Geospatial development links your data to places on the Earth's surface. Its analysis is used in almost every industry to answer location type questions. Combined with the power of the Python programming language, which is becoming the de facto spatial scripting choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems. This book begins by tackling the installation of the necessary software dependencies and libraries needed to perform spatial analysis with Python. From there, the next logical step is to prepare our data for analysis; we will do this by building up our tool box to deal with data preparation, transformations, and projections. Now that our data is ready for analysis, we will tackle the most common analysis methods for vector and raster data. To check or validate our results, we will explore how to use topology checks to ensure top-quality results. This is followed with network routing analysis focused on constructing indoor routes within buildings, over different levels. Finally, we put several recipes together in a GeoDjango web application that demonstrates a working indoor routing spatial analysis application. The round trip will provide you all the pieces you need to accomplish your own spatial analysis application to suit your requirements. Style and approach Easy-to-follow, step-by-step recipes, explaining from start to finish how to accomplish real-world tasks.
Learning Geospatial Analysis With Python
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Author : Joel Lawhead
language : en
Publisher: Packt Publishing Ltd
Release Date : 2013-10-25
Learning Geospatial Analysis With Python written by Joel Lawhead and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-25 with Computers categories.
This is a tutorial-style book that helps you to perform Geospatial and GIS analysis with Python and its tools/libraries. This book will first introduce various Python-related tools/packages in the initial chapters before moving towards practical usage, examples, and implementation in specialized kinds of Geospatial data analysis.This book is for anyone who wants to understand digital mapping and analysis and who uses Python or another scripting language for automation or crunching data manually.This book primarily targets Python developers, researchers, and analysts who want to perform Geospatial, modeling, and GIS analysis with Python.
Qgis Python Programming Cookbook
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Author : Joel Lawhead
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-03-14
Qgis Python Programming Cookbook written by Joel Lawhead and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-14 with Computers categories.
Master over 170 recipes that will help you turn QGIS from a desktop GIS tool into a powerful automated geospatial framework About This Book Delve into the undocumented features of the QGIS API Get a set of user-friendly recipes that can automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes This book has a complete code upgrade to QGIS 2.18 and 30 new, valuable recipes Who This Book Is For This book is for geospatial analysts who want to learn more about automating everyday GIS tasks as well as programmers responsible for building GIS applications. The short, reusable recipes make concepts easy to understand and combine so you can build larger applications that are easy to maintain. What You Will Learn Use Python and QGIS to produce captivating GIS visualizations and build complex map layouts Find out how to effectively use the poorly-documented and undocumented features of the QGIS Python API Automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes Create, import, and edit geospatial data on disk or in-memory Change QGIS settings programmatically to control default behavior Automatically generate PDF map books Build dynamic forms for field input In Detail QGIS is a desktop geographic information system that facilitates data viewing, editing, and analysis. Paired with the most efficient scripting language—Python, we can write effective scripts that extend the core functionality of QGIS. Based on version QGIS 2.18, this book will teach you how to write Python code that works with spatial data to automate geoprocessing tasks in QGIS. It will cover topics such as querying and editing vector data and using raster data. You will also learn to create, edit, and optimize a vector layer for faster queries, reproject a vector layer, reduce the number of vertices in a vector layer without losing critical data, and convert a raster to a vector. Following this, you will work through recipes that will help you compose static maps, create heavily customized maps, and add specialized labels and annotations. As well as this, we'll also share a few tips and tricks based on different aspects of QGIS. Style and approach This book follows a recipe-based problem-solution approach to address and dispel challenges faced when implementing and using QGIS on a regular basis.
Learning Geospatial Analysis With Python
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Author : Joel Lawhead
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-11-24
Learning Geospatial Analysis With Python written by Joel Lawhead and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-24 with Technology & Engineering categories.
Harness the powerful Python programming language to navigate the realms of geographic information systems, remote sensing, topography, and more, while embracing a guiding framework for effective geospatial analysis Key Features Create GIS solutions using the new features introduced in Python 3.10 Explore a range of GIS tools and libraries, including PostGIS, QGIS, and PROJ Identify the tools and resources that best align with your specific needs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGeospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. In this special 10th anniversary edition, you'll embark on an exhilarating geospatial analysis adventure using Python. This fourth edition starts with the fundamental concepts, enhancing your expertise in geospatial analysis processes with the help of illustrations, basic formulas, and pseudocode for real-world applications. As you progress, you’ll explore the vast and intricate geospatial technology ecosystem, featuring thousands of software libraries and packages, each offering unique capabilities and insights. This book also explores practical Python GIS geospatial applications, remote sensing data, elevation data, and the dynamic world of geospatial modeling. It emphasizes the predictive and decision-making potential of geospatial technology, allowing you to visualize complex natural world concepts, such as environmental conservation, urban planning, and disaster management to make informed choices. You’ll also learn how to leverage Python to process real-time data and create valuable information products. By the end of this book, you'll have acquired the knowledge and techniques needed to build a complete geospatial application that can generate a report and can be further customized for different purposes.What you will learn Automate geospatial analysis workflows using Python Understand the different formats in which geospatial data is available Unleash geospatial tech tools to create stunning visualizations Create thematic maps with Python tools such as PyShp, OGR, and the Python Imaging Library Build a geospatial Python toolbox for analysis and application development Unlock remote sensing secrets, detect changes, and process imagery Leverage ChatGPT for solving Python geospatial solutions Apply geospatial analysis to real-time data tracking and storm chasing Who this book is for This book is for Python developers, researchers, or analysts who want to perform geospatial modeling and GIS analysis with Python. Basic knowledge of digital mapping and analysis using Python or other scripting languages will be helpful.
Programming Arcgis 10 1 With Python Cookbook
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Author : Eric Pimpler
language : en
Publisher: Packt Pub Limited
Release Date : 2013
Programming Arcgis 10 1 With Python Cookbook written by Eric Pimpler and has been published by Packt Pub Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.
This book is written in a helpful, practical style with numerous hands-on recipes and chapters to help you save time and effort by using Python to power ArcGIS to create shortcuts, scripts, tools, and customizations."Programming ArcGIS 10.1 with Python Cookbook" is written for GIS professionals who wish to revolutionize their ArcGIS workflow with Python. Basic Python or programming knowledge is essential(?).
Pandas Cookbook
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Author : Theodore Petrou
language : en
Publisher:
Release Date : 2017-10-23
Pandas Cookbook written by Theodore Petrou and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-23 with Computers categories.
Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysisAbout This Book* Use the power of pandas to solve most complex scientific computing problems with ease* Leverage fast, robust data structures in pandas to gain useful insights from your data* Practical, easy to implement recipes for quick solutions to common problems in data using pandasWho This Book Is ForThis book is for data scientists, analysts and Python developers who wish to explore data analysis and scientific computing in a practical, hands-on manner. The recipes included in this book are suitable for both novice and advanced users, and contain helpful tips, tricks and caveats wherever necessary. Some understanding of pandas will be helpful, but not mandatory.What You Will Learn* Master the fundamentals of pandas to quickly begin exploring any dataset* Isolate any subset of data by properly selecting and querying the data* Split data into independent groups before applying aggregations and transformations to each group* Restructure data into tidy form to make data analysis and visualization easier* Prepare real-world messy datasets for machine learning* Combine and merge data from different sources through pandas SQL-like operations* Utilize pandas unparalleled time series functionality* Create beautiful and insightful visualizations through pandas direct hooks to Matplotlib and SeabornIn DetailThis book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way.The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter.Many advanced recipes combine several different features across the pandas library to generate results.Style and approachThe author relies on his vast experience teaching pandas in a professional setting to deliver very detailed explanations for each line of code in all of the recipes. All code and dataset explanations exist in Jupyter Notebooks, an excellent interface for exploring data.
Qgis Python Programming Cookbook Second Edition
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Author : Joel Lawhead
language : en
Publisher:
Release Date : 2017-03-10
Qgis Python Programming Cookbook Second Edition written by Joel Lawhead and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-10 with Computers categories.
Master over 170 recipes that will help you turn QGIS from a desktop GIS tool into a powerful automated geospatial frameworkAbout This Book* Delve into the undocumented features of the QGIS API* Get a set of user-friendly recipes that can automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes* This book has a complete code upgrade to QGIS 2.18 and 30 new, valuable recipesWho This Book Is ForThis book is for geospatial analysts who want to learn more about automating everyday GIS tasks as well as programmers responsible for building GIS applications. The short, reusable recipes make concepts easy to understand and combine so you can build larger applications that are easy to maintain.What You Will Learn* Use Python and QGIS to produce captivating GIS visualizations and build complex map layouts* Find out how to effectively use the poorly-documented and undocumented features of the QGIS Python API* Automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes* Create, import, and edit geospatial data on disk or in-memory* Change QGIS settings programmatically to control default behavior * Automatically generate PDF map books * Build dynamic forms for field inputIn DetailQGIS is a desktop geographic information system that facilitates data viewing, editing, and analysis. Paired with the most efficient scripting language--Python, we can write effective scripts that extend the core functionality of QGIS. Based on version QGIS 2.18, this book will teach you how to write Python code that works with spatial data to automate geoprocessing tasks in QGIS. It will cover topics such as querying and editing vector data and using raster data. You will also learn to create, edit, and optimize a vector layer for faster queries, reproject a vector layer, reduce the number of vertices in a vector layer without losing critical data, and convert a raster to a vector. Following this, you will work through recipes that will help you compose static maps, create heavily customized maps, and add specialized labels and annotations. As well as this, we'll also share a few tips and tricks based on different aspects of QGIS.Style and approachThis book follows a recipe-based problem-solution approach to address and dispel challenges faced when implementing and using QGIS on a regular basis.
Artificial Intelligence With Python
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Author : Prateek Joshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-01-27
Artificial Intelligence With Python written by Prateek Joshi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with Computers categories.
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
Learn Python By Building Data Science Applications
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Author : Philipp Kats
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-08-30
Learn Python By Building Data Science Applications written by Philipp Kats and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-30 with Computers categories.
Understand the constructs of the Python programming language and use them to build data science projects Key FeaturesLearn the basics of developing applications with Python and deploy your first data applicationTake your first steps in Python programming by understanding and using data structures, variables, and loopsDelve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in PythonBook Description Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards. What you will learnCode in Python using Jupyter and VS CodeExplore the basics of coding – loops, variables, functions, and classesDeploy continuous integration with Git, Bash, and DVCGet to grips with Pandas, NumPy, and scikit-learnPerform data visualization with Matplotlib, Altair, and DatashaderCreate a package out of your code using poetry and test it with PyTestMake your machine learning model accessible to anyone with the web APIWho this book is for If you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.