Are you new to SciPy and NumPy? Do you want to learn it quickly and easily through examples and a concise introduction?
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 operationsSolve minimization problems quickly with SciPy’s optimization packageUse SciPy functions for interpolation, from simple univariate to complex multivariate casesApply a variety of SciPy statistical tools such as distributions and functionsLearn SciPy’s spatial and cluster analysis classesSave operation time and memory usage with sparse matrices
