Elegant Scipy

Welcome to Scientific Python and its community! With this practical book, you'll learn the fundamental parts of SciPy and related libraries, and get a taste of beautiful, easy-to-read code that you can use in practice. More and more scientists are programming, and the SciPy library is here to help.

Finding useful functions and using them correctly, efficiently, and in easily readable code are two very different things. You'll learn by example with some of the best code available, selected to cover a wide range of SciPy and related libraries—including scikit-learn, scikit-image, toolz, and pandas.

The examples highlight clever, elegant uses of advanced features of NumPy, SciPy, and related libraries. Beginners will learn not the functionality of the library, but its application to real world problems. This book starts from first principles and provides all of the necessary background to understand each example, including idioms, libraries, and scientific concepts.

Juan Nunez-Iglesias is a Research Scientist at the Life Sciences Computation Centre in Melbourne, Australia. Prior positions include Research Associate at HHMI Janelia Farm (where he worked with Mitya Chklovskii) and Research Assistant / PhD student at the University of Southern California (where he studied computational biology supervised by Xianghong Jasmine Zhou). His principal research interests are neuroscience and image analysis. He is also interested in graph methods in bioinformatics, and in biostatistics.

Stéfan van der Walt is an assistant researcher at the BerkeleyInstitute for Data Science at the University of California, Berkeleyand a senior lecturer in applied mathematics at Stellenbosch University, South Africa. He has been involved in the development of scientific open source software for more than a decade, and enjoys teaching Python at workshops and conferences. Stéfan is the founder of scikit-image and a contributor to numpy, scipy and dipy.

Harriet Dashnow is a bioinformatician and has worked at the Murdoch Childrens Research Institute, the Department of Biochemistry at the University of Melbourne and the Victorian Life Sciences Computation Initiative (VLSCI). Harriet obtained a BA (Psychology), a BS (Genetics and Biochemistry), and a MS (Bioinformatics) from the University of Melbourne. She is currently working towards a PhD. She organises and teaches computational skills workshops in such areas as genomics, Software Carpentry, Python, R, Unix and Git version control.