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Publicado por Sage Publications Ltd, GB, 2020
ISBN 10: 1526449366 ISBN 13: 9781526449368
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Añadir al carritoPaperback. Condición: New. We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial - it is collected some-where - and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges.Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a 'learning by doing' textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
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Publicado por Sage Publications Ltd, GB, 2020
ISBN 10: 1526449366 ISBN 13: 9781526449368
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Añadir al carritoPaperback. Condición: New. We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial - it is collected some-where - and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges.Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a 'learning by doing' textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
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Publicado por SAGE Publications Ltd 2021-01-09, 2021
ISBN 10: 1526449366 ISBN 13: 9781526449368
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Publicado por Sage Publications Ltd, GB, 2020
ISBN 10: 1526449366 ISBN 13: 9781526449368
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Añadir al carritoPaperback. Condición: New. We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial - it is collected some-where - and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges.Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a 'learning by doing' textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
Publicado por Sage Publications Ltd, GB, 2020
ISBN 10: 1526449366 ISBN 13: 9781526449368
Idioma: Inglés
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
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Añadir al carritoPaperback. Condición: New. We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial - it is collected some-where - and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges.Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a 'learning by doing' textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Über den AutorAlexis Comber, Lex, is Professor of Spatial Data Analytics at Leeds Institute for Data Analytics (LIDA) the University of Leeds. He worked previously at the University of Leicester where he held a chair in Geographi.
Publicado por Sage Publications Ltd, London, 2020
ISBN 10: 1526449366 ISBN 13: 9781526449368
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 92,05
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Añadir al carritoPaperback. Condición: new. Paperback. We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial - it is collected some-where - and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges.Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a 'learning by doing' textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Publicado por Sage Publications Ltd, London, 2020
ISBN 10: 1526449366 ISBN 13: 9781526449368
Idioma: Inglés
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Añadir al carritoPaperback. Condición: new. Paperback. We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial - it is collected some-where - and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges.Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a 'learning by doing' textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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