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Aggiungi al carrelloCondizione: New. Gain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to .
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - Gain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to terabytes.Through real-world examples and practical exercises, you'll explore topics such as scientific datasets, hierarchically organized groups, user-defined metadata, and interoperable files. Examples are applicable for users of both Python 2 and Python 3. If you're familiar with the basics of Python data analysis, this is an ideal introduction to HDF5. Get set up with HDF5 tools and create your first HDF5 file Work with datasets by learning the HDF5 Dataset object Understand advanced features like dataset chunking and compression Learn how to work with HDF5's hierarchical structure, using groups Create self-describing files by adding metadata with HDF5 attributes Take advantage of HDF5's type system to create interoperable files Express relationships among data with references, named types, and dimension scales Discover how Python mechanisms for writing parallel code interact with HDF5.
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Aggiungi al carrelloCondizione: New. Gain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to terabytes. Num Pages: 142 pages, illustrations. BIC Classification: UMW. Category: (XV) Technical / Manuals. Dimension: 234 x 178 x 9. Weight in Grams: 276. . 2013. 1st Edition. Paperback. . . . .
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Aggiungi al carrelloPaperback. Condizione: Brand New. 142 pages. 9.19x7.00x0.40 inches. In Stock.
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Aggiungi al carrelloCondizione: New. Gain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to terabytes. Num Pages: 142 pages, illustrations. BIC Classification: UMW. Category: (XV) Technical / Manuals. Dimension: 234 x 178 x 9. Weight in Grams: 276. . 2013. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.
Editore: O'Reilly Media (edition 1), 2013
ISBN 10: 1449367836 ISBN 13: 9781449367831
Lingua: Inglese
Da: BooksRun, Philadelphia, PA, U.S.A.
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Aggiungi al carrellopaperback. Condizione: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Aggiungi al carrellopaperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Da: Revaluation Books, Exeter, Regno Unito
EUR 33,33
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Aggiungi al carrelloPaperback. Condizione: Brand New. 142 pages. 9.19x7.00x0.40 inches. In Stock. This item is printed on demand.