SciPy and NumPy /

Are you new to SciPy and NumPy? Do you want to learn it quickly and easily through examples and a concise introduction? Then this is the book for you. You’ll cut through the complexity of online documentation and discover how easily you can get up to speed with these Python libraries. Ideal for data...

Ausführliche Beschreibung

Gespeichert in:
1. Verfasser:
Bressert, Eli
Format:
Elektronisch E-Book
Sprache:
Englisch
Veröffentlicht:
Sebastopol, California : O'Reilly, 2013.
Ausgabe:
1st edition
Zusammenfassung:
Are you new to SciPy and NumPy? Do you want to learn it quickly and easily through examples and a concise introduction? Then this is the book for you. You’ll cut through the complexity of online documentation and discover how easily you can get up to speed with these Python libraries. Ideal for data analysts and scientists in any field, this overview shows you how to use NumPy for numerical processing, including array indexing, math operations, and loading and saving data. You’ll learn how SciPy helps you work with advanced mathematical functions such as optimization, interpolation, integration, clustering, statistics, and other tools that take scientific programming to a whole new level. The new edition is now available, fully revised and updated in June 2013. Learn the capabilities of NumPy arrays, element-by-element operations, and core mathematical operations Solve minimization problems quickly with SciPy’s optimization package Use SciPy functions for interpolation, from simple univariate to complex multivariate cases Apply a variety of SciPy statistical tools such as distributions and functions Learn SciPy’s spatial and cluster analysis classes Save operation time and memory usage with sparse matrices
Umfang:
1 online resource (81 p.)
text file
Anmerkungen:
Bibliographic Level Mode of Issuance: Monograph
Anmerkungen:
English
ISBN:
9781449361624
1449361625
9781306810395
1306810396
9781449361631
1449361633
Schlagworte:
Numerical analysis.
Python (Computer program language)
Bezugswerke:
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