Python and HDF5
Andrew ColletteGain 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.
Година:
2013
Издателство:
O'Reilly Media
Език:
english
ISBN 10:
1449367828
ISBN 13:
9781449367824
Файл:
EPUB, 1.84 MB
IPFS:
,
english, 2013