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Python Geospatial Development - Third Edition
Develop sophisticated mapping applications from scratch using Python 3 tools for geospatial developmentAbout This Book• Build web applications based around maps and geospatial data using Python 3.x• Install and use various toolkits and obtain geospatial data for use in your programs• This practical, hands-on book will teach you all about geospatial development in PythonWho This Book Is ForThis book is for experienced Python developers who want to learn about geospatial concepts, obtain and work with geospatial data, solve spatial problems, and build sophisticated map-based applications using Python.What You Will Learn• Access, manipulate, and display geospatial data from within your Python programs• Master the core geospatial concepts of location, distance, units, projections, and datums• Read and write geospatial data in both vector and raster format• Perform complex, real-world geospatial calculations using Python• Store and access geospatial information in a database• Use points, lines, and polygons within your Python programs• Convert geospatial data into attractive maps using Python-based tools• Build complete web-based mapping applications using PythonIn DetailGeospatial development links your data to locations on the surface of the Earth. Writing geospatial programs involves tasks such as grouping data by location, storing and analyzing large amounts of spatial information, performing complex geospatial calculations, and drawing colorful interactive maps. In order to do this well, you'll need appropriate tools and techniques, as well as a thorough understanding of geospatial concepts such as map projections, datums, and coordinate systems.This book provides an overview of the major geospatial concepts, data sources, and toolkits. It starts by showing you how to store and access spatial data using Python, how to perform a range of spatial calculations, and how to store spatial data in a database. Further on, the book teaches you how to build your own slippy map interface within a web application, and finishes with the detailed construction of a geospatial data editor using the GeoDjango framework.By the end of this book, you will be able to confidently use Python to write your own geospatial applications ranging from quick, one-off utilities to sophisticated web-based applications using maps and other geospatial data.Style and approach This book is a comprehensive course in geospatial development. The concepts you need to know are presented in a hands-on fashion with example code to help you to solve real-world problems right away. Larger programs are built up step by step while guiding you through the process of building your own sophisticated mapping applications.
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Learning Geospatial Analysis with Python -
An effective guide to geographic information systems and remote sensing analysis using Python 3About This Book• Construct applications for GIS development by exploiting Python• This focuses on built-in Python modules and libraries compatible with the Python Packaging Index distribution system—no compiling of C libraries necessary• This practical, hands-on tutorial teaches you all about Geospatial analysis in Python Who This Book Is ForIf you are a Python developer, researcher, or analyst who wants to perform Geospatial, modeling, and GIS analysis with Python, then this book is for you. Familarity with digital mapping and analysis using Python or another scripting language for automation or crunching data manually is appreciatedWhat You Will Learn• Automate Geospatial analysis workflows using Python• Code the simplest possible GIS in 60 lines of Python• Mold thematic maps with Python tools• Get hold of the various forms that geospatial data comes in• Produce elevation contours using Python tools• Create flood inundation models• Apply Geospatial analysis to find out about real-time data tracking and for storm chasingIn DetailGeospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software.Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data.This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don't become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.Style and approach This is a practical, hands-on tutorial that teaches you all about Geospatial analysis interactively using Python.
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Mastering Predictive Analytics with Python
Exploit the power of data in your business by building advanced predictive modeling applications with PythonAbout This Book• Master open source Python tools to build sophisticated predictive models• Learn to identify the right machine learning algorithm for your problem with this forward-thinking guide• Grasp the major methods of predictive modeling and move beyond the basics to a deeper level of understandingWho This Book Is ForThis book is designed for business analysts, BI analysts, data scientists, or junior level data analysts who are ready to move from a conceptual understanding of advanced analytics to an expert in designing and building advanced analytics solutions using Python. You're expected to have basic development experience with Python.What You Will Learn • Gain an insight into components and design decisions for an analytical application• Master the use Python notebooks for exploratory data analysis and rapid prototyping• Get to grips with applying regression, classification, clustering, and deep learning algorithms• Discover the advanced methods to analyze structured and unstructured data• Find out how to deploy a machine learning model in a production environment• Visualize the performance of models and the insights they produce• Scale your solutions as your data grows using Python• Ensure the robustness of your analytic applications by mastering the best practices of predictive analysisIn DetailThe volume, diversity, and speed of data available has never been greater. Powerful machine learning methods can unlock the value in this information by finding complex relationships and unanticipated trends. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications to deliver insights that are of tremendous value to their organizations.In Mastering Predictive Analytics with Python, you will learn the process of turning raw data into powerful insights. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications and how to quickly apply these methods to your own data to create robust and scalable prediction services.Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates not only how these methods work, but how to implement them in practice. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring the insights of predictive modeling to lifeStyle and approach This book emphasizes on explaining methods through example data and code, showing you templates that you can quickly adapt to your own use cases. It focuses on both a practical application of sophisticated algorithms and the intuitive understanding necessary to apply the correct method to the problem at hand. Through visual examples, it also demonstrates how to
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wxPython Application Development Cookbook
Over 80 step-by-step recipes to get you up to speed with building your own wxPython applicationsAbout This Book• This book empowers you to create rich cross-platform graphical user interfaces using Python• It helps you develop applications that can be deployed on Windows, OSX, and Linux• The recipes in the book involve real-world applications, giving you a first-hand experience of the practical scenariosWho This Book Is ForFor those who are familiar with programming in Python and want to start building applications with graphical user interfaces, this book will get you up and running quickly. A basic understanding of the Python programming language and object-oriented concepts are all that is needed.What You Will Learn• Create full featured user interfaces• Design and develop custom controls• Deploy and distribute wxPython applications to Windows, Macintosh OS X, Linux, and other UNIX-like environments• Handle and respond to application events• Manage and display data using grids• Interact with web services from your GUI• Use Paint events to draw custom displays• Support the display of user interfaces in multiple languagesIn DetailwxPython is a GUI toolkit for the Python programming language built on top of the cross-platform wxWidgets GUI libraries. wxPython provides a powerful set of tools that allow you to quickly and efficiently building applications that can run on a variety of different platforms. Since wxWidgets provides a wrapper around each platform's native GUI toolkit, the applications built with wxPython will have a native look and feel wherever they are deployed.This book will provide you with the skills to build highly functional and native looking user interfaces for Python applications on multiple operating system environments. By working through the recipes, you will gain insights into and exposure to creating applications using wxPython. With a wide range of topics covered in the book, there are recipes to get the most basic of beginners started in GUI programming as well as tips to help experienced users get more out of their applications. The recipes will take you from the most basic application constructs all the way through to the deployment of complete applications.Style and approach This book is a collection of step-by-step recipes that introduce the various components and concepts of wxPython in a conversational and easy-to-follow way. Each recipe contains coded examples along with detailed explanations about the key points of each topic. Each topic is designed to introduce and show you how to use a single feature from the wxPython library.
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Statistics and Calculus with Python Workshop
With examples and activities that help you achieve real results, applying calculus and statistical methods relevant to advanced data science has never been so easyKey FeaturesDiscover how most programmers use the main Python libraries when performing statistics with PythonUse descriptive statistics and visualizations to answer business and scientific questionsSolve complicated calculus problems, such as arc length and solids of revolution using derivatives and integralsBook DescriptionAre you looking to start developing artificial intelligence applications? Do you need a refresher on key mathematical concepts? Full of engaging practical exercises, The Statistics and Calculus with Python Workshop will show you how to apply your understanding of advanced mathematics in the context of Python.The book begins by giving you a high-level overview of the libraries you'll use while performing statistics with Python. As you progress, you'll perform various mathematical tasks using the Python programming language, such as solving algebraic functions with Python starting with basic functions, and then working through transformations and solving equations. Later chapters in the book will cover statistics and calculus concepts and how to use them to solve problems and gain useful insights. Finally, you'll study differential equations with an emphasis on numerical methods and learn about algorithms that directly calculate values of functions.By the end of this book, you'll have learned how to apply essential statistics and calculus concepts to develop robust Python applications that solve business challenges.What you will learnGet to grips with the fundamental mathematical functions in PythonPerform calculations on tabular datasets using pandasUnderstand the differences between polynomials, rational functions, exponential functions, and trigonometric functionsUse algebra techniques for solving systems of equationsSolve real-world problems with probabilitySolve optimization problems with derivatives and integralsWho this book is forIf you are a Python programmer who wants to develop intelligent solutions that solve challenging business problems, then this book is for you. To better grasp the concepts explained in this book, you must have a thorough understanding of advanced mathematical concepts, such as Markov chains, Euler's formula, and Runge-Kutta methods as the book only explains how these techniques and concepts can be implemented in Python.
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