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008    140116s2013    cau     o     000 0 eng d 
019    863150688|a868236027|a968115838|a969039213 
020    9781491945001|q(electronic bk.) 
020    1491945001|q(electronic bk.) 
020    9781491944981 
020    1491944986 
020    9781491945018 
020    149194501X 
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049    INap 
082 04 005.13/3|b23 
082 04 005.13/3|b23|222 
099    eBook O'Reilly for Public Libraries 
100 1  Collette, Andrew. 
245 10 Python and HDF5 /|cAndrew Collette.|h[O'Reilly electronic 
       resource] 
264  1 Sebastopol, Calif. :|bO'Reilly Media, Inc.,|c2013. 
264  4 |c©2014 
300    1 online resource (135 pages) 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file 
520    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. 
588 0  Print version record. 
590    O'Reilly|bO'Reilly Online Learning: Academic/Public 
       Library Edition 
650  0 Python (Computer program language) 
650  0 Mathematics|xData processing. 
650  6 Python (Langage de programmation) 
650  6 Mathématiques|xInformatique. 
650  7 Mathematics|xData processing|2fast 
650  7 Python (Computer program language)|2fast 
776 08 |iPrint version:|aCollette, Andrew.|tPython and HDF5
       |z1449367836|w(OCoLC)859383794 
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/library/view/~/9781491944981/?ar
       |zAvailable on O'Reilly for Public Libraries 
938    ProQuest Ebook Central|bEBLB|nEBL1489987 
938    EBSCOhost|bEBSC|n654684 
938    YBP Library Services|bYANK|n11305400 
938    YBP Library Services|bYANK|n11323948 
994    92|bJFN