Name: Python and HDF5: Unlocking Scientific Data
Price: 1002.00 TWD
Availability: InStock
Author: Collette, Andrew
ISBN: 9781449367831

portada Python and HDF5: Unlocking Scientific Data

Python and HDF5: Unlocking Scientific Data

Type

Physical Book

Author

Andrew Collette

Publisher

O'Reilly Media

Language

English

Format

Paperback

Dimensions

23.2 x 18.0 x 0.8 cm

Weight

0.26 kg.

ISBN13

9781449367831

Synopsis "Python and HDF5: Unlocking Scientific Data"

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 fileWork with datasets by learning the HDF5 Dataset objectUnderstand advanced features like dataset chunking and compressionLearn how to work with HDF5's hierarchical structure, using groupsCreate self-describing files by adding metadata with HDF5 attributesTake advantage of HDF5's type system to create interoperable filesExpress relationships among data with references, named types, and dimension scalesDiscover how Python mechanisms for writing parallel code interact with HDF5

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Python and HDF5: Unlocking Scientific Data - Collette, Andrew

Synopsis "Python and HDF5: Unlocking Scientific Data"

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