python geospatial data analysis von mcclain bonny (30 Ergebnisse)

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Paperback or Softback. Zustand: New. Python for Geospatial Data Analysis: Theory, Tools, and Practice for Location Intelligence 1.34. Book.

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

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Paperback. Zustand: New. In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions.Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python.This book helps you:Understand the importance of applying spatial relationships in data scienceSelect and apply data layering of both raster and vector graphicsApply location data to leverage spatial analyticsDesign informative and accurate mapsAutomate geographic data with Python scriptsExplore Python packages for additional functionalityWork with atypical data types such as polygons, shape files, and projectionsUnderstand the graphical syntax of spatial data science to stimulate curiosity.

Paperback. Zustand: new. Paperback. In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. This book helps you: Understand the importance of applying spatial relationships in data science Select and apply data layering of both raster and vector graphics Apply location data to leverage spatial analytics Design informative and accurate maps Automate geographic data with Python scripts Explore Python packages for additional functionality Work with atypical data types such as polygons, shape files, and projections Understand the graphical syntax of spatial data science to stimulate curiosity" With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days. 209.

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Paperback. Zustand: New.

Paperback. Zustand: New. In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions.Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python.This book helps you:Understand the importance of applying spatial relationships in data scienceSelect and apply data layering of both raster and vector graphicsApply location data to leverage spatial analyticsDesign informative and accurate mapsAutomate geographic data with Python scriptsExplore Python packages for additional functionalityWork with atypical data types such as polygons, shape files, and projectionsUnderstand the graphical syntax of spatial data science to stimulate curiosity.

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Zustand: New. 2022. Paperback. . . . . .

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Paperback. Zustand: New. In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions.Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python.This book helps you:Understand the importance of applying spatial relationships in data scienceSelect and apply data layering of both raster and vector graphicsApply location data to leverage spatial analyticsDesign informative and accurate mapsAutomate geographic data with Python scriptsExplore Python packages for additional functionalityWork with atypical data types such as polygons, shape files, and projectionsUnderstand the graphical syntax of spatial data science to stimulate curiosity.

Paperback. Zustand: Brand New. 200 pages. 9.19x7.00x0.77 inches. In Stock.

Paperback. Zustand: new. Paperback. In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. This book helps you: Understand the importance of applying spatial relationships in data science Select and apply data layering of both raster and vector graphics Apply location data to leverage spatial analytics Design informative and accurate maps Automate geographic data with Python scripts Explore Python packages for additional functionality Work with atypical data types such as polygons, shape files, and projections Understand the graphical syntax of spatial data science to stimulate curiosity" With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Zustand: New. &Uumlber den AutorDr. Bonny P McClain is a member of the National Press Club, 500 Women Scientists, and Investigational Reporters and Editors allowing access to a wide variety of health policy and health economic discussions. Bonny .

Paperback. Zustand: new. Paperback. In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. This book helps you: Understand the importance of applying spatial relationships in data science Select and apply data layering of both raster and vector graphics Apply location data to leverage spatial analytics Design informative and accurate maps Automate geographic data with Python scripts Explore Python packages for additional functionality Work with atypical data types such as polygons, shape files, and projections Understand the graphical syntax of spatial data science to stimulate curiosity" With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Zustand: New. In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions.Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python.This book helps you:Understand the importance of applying spatial relationships in data scienceSelect and apply data layering of both raster and vector graphicsApply location data to leverage spatial analyticsDesign informative and accurate mapsAutomate geographic data with Python scriptsExplore Python packages for additional functionalityWork with atypical data types such as polygons, shape files, and projectionsUnderstand the graphical syntax of spatial data science to stimulate curiosity.

Taschenbuch. Zustand: Neu. Neuware - With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions.

Paperback / softback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 209.

Paperback. Zustand: Brand New. 200 pages. 9.19x7.00x0.77 inches. In Stock. This item is printed on demand.