[PDF.50tc] Python and HDF5: Unlocking Scientific Data
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Python and HDF5: Unlocking Scientific Data
Andrew Collette
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| #848358 in Books | O Reilly Media | 2013-11-11 | 2013-11-11 | Original language:English | PDF # 1 | 9.19 x.30 x7.00l,.57 | File type: PDF | 152 pages | O Reilly Media||0 of 0 people found the following review helpful.| Five Stars|By LPO|Excellent discussion and demonstration of the combination of 2 big data powerhouse technologies. Very well written and accessible.|0 of 0 people found the following review helpful.| Four Stars|By Jose Luis Villarreal Benitez|thanks|13 of 13 people found the following review helpful.|About the Author|
|Andrew Collette holds a Ph.D. in physics from UCLA, and works as a laboratory research scientist at the University of Colorado. He has worked with the Python-NumPy-HDF5 stack at two multimillion-dollar research facilities; the first being
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. Ex...
You can specify the type of files you want, for your device.Python and HDF5: Unlocking Scientific Data | Andrew Collette. I really enjoyed this book and have already told so many people about it!
