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

� propos de l?auteur

Eli Bressert is a PhD astrophysics student, Chandra Science Imager, and contributor to astrobetter.com and astropython.org. He develops Python apps like ATpy, APLpy, and Luj.

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