ISBN: 9781032445953 - geographic data science with python (chapman & hall/crc texts in statistical science) (33 resultados)

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Paperback. Condición: new. Paperback. This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data.Key Features: Showcases the excellent data science environment in Python. Provides examples for readers to replicate, adapt, extend, and improve. Covers the crucial knowledge needed by geographic data scientists.It presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts.Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field. This book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data. The book is structured around the excellent data science environment in Python. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New.

Condición: New.

Paperback. Condición: New. This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data.Key Features:Showcases the excellent data science environment in PythonProvides examples for readers to replicate, adapt, extend, and improveCovers the crucial knowledge needed by geographic data scientistsIt presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts.Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field.…

Paperback. Condición: New. This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data.Key Features:Showcases the excellent data science environment in PythonProvides examples for readers to replicate, adapt, extend, and improveCovers the crucial knowledge needed by geographic data scientistsIt presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts.Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field.…

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Condición: New. 1st edition NO-PA16APR2015-KAP.

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Paperback. Condición: new. Paperback. This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data.Key Features: Showcases the excellent data science environment in Python. Provides examples for readers to replicate, adapt, extend, and improve. Covers the crucial knowledge needed by geographic data scientists.It presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts.Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field. This book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data. The book is structured around the excellent data science environment in Python. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condición: New. 2023. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

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Paperback. Condición: Brand New. 416 pages. 9.19x6.13x1.06 inches. In Stock.

Condición: New. Sergio Rey is Professor of Geography and Founding Director of the Center for Open Geographical Science at San Diego State University. Rey is the creator and lead developer of the open source package STARS: Space-Time Analysis of Regional Systems a.

Soft cover. Condición: New. 1st Edition.

Soft cover. Condición: New. 1st Edition.

Paperback. Condición: New. This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data.Key Features:Showcases the excellent data science environment in PythonProvides examples for readers to replicate, adapt, extend, and improveCovers the crucial knowledge needed by geographic data scientistsIt presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts.Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field.…

Paperback. Condición: New. This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data.Key Features:Showcases the excellent data science environment in PythonProvides examples for readers to replicate, adapt, extend, and improveCovers the crucial knowledge needed by geographic data scientistsIt presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts.Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field.…

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Paperback. Condición: Brand New. 416 pages. 9.19x6.13x1.06 inches. In Stock. This item is printed on demand.