SciPy and NumPy
Author | : Eli Bressert |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 68 |
Release | : 2012 |
Genre | : Computers |
ISBN | : 1449305466 |
"Optimizing and boosting your Python programming"--Cover.
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Author | : Eli Bressert |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 68 |
Release | : 2012 |
Genre | : Computers |
ISBN | : 1449305466 |
"Optimizing and boosting your Python programming"--Cover.
Author | : Juan Nunez-Iglesias |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 277 |
Release | : 2017-08-11 |
Genre | : Computers |
ISBN | : 1491922958 |
Welcome to Scientific Python and its community. If you’re a scientist who programs with Python, this practical guide not only teaches you the fundamental parts of SciPy and libraries related to it, but also gives you a taste for beautiful, easy-to-read code that you can use in practice. You’ll learn how to write elegant code that’s clear, concise, and efficient at executing the task at hand. Throughout the book, you’ll work with examples from the wider scientific Python ecosystem, using code that illustrates principles outlined in the book. Using actual scientific data, you’ll work on real-world problems with SciPy, NumPy, Pandas, scikit-image, and other Python libraries. Explore the NumPy array, the data structure that underlies numerical scientific computation Use quantile normalization to ensure that measurements fit a specific distribution Represent separate regions in an image with a Region Adjacency Graph Convert temporal or spatial data into frequency domain data with the Fast Fourier Transform Solve sparse matrix problems, including image segmentations, with SciPy’s sparse module Perform linear algebra by using SciPy packages Explore image alignment (registration) with SciPy’s optimize module Process large datasets with Python data streaming primitives and the Toolz library
Author | : Travis Oliphant |
Publisher | : CreateSpace |
Total Pages | : 364 |
Release | : 2015-09-15 |
Genre | : |
ISBN | : 9781517300074 |
This is the second edition of Travis Oliphant's A Guide to NumPy originally published electronically in 2006. It is designed to be a reference that can be used by practitioners who are familiar with Python but want to learn more about NumPy and related tools. In this updated edition, new perspectives are shared as well as descriptions of new distributed processing tools in the ecosystem, and how Numba can be used to compile code using NumPy arrays. Travis Oliphant is the co-founder and CEO of Continuum Analytics. Continuum Analytics develops Anaconda, the leading modern open source analytics platform powered by Python. Travis, who is a passionate advocate of open source technology, has a Ph.D. from Mayo Clinic and B.S. and M.S. degrees in Mathematics and Electrical Engineering from Brigham Young University. Since 1997, he has worked extensively with Python for computational and data science. He was the primary creator of the NumPy package and founding contributor to the SciPy package. He was also a co-founder and past board member of NumFOCUS, a non-profit for reproducible and accessible science that supports the PyData stack. He also served on the board of the Python Software Foundation.
Author | : Jake VanderPlas |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 609 |
Release | : 2016-11-21 |
Genre | : Computers |
ISBN | : 1491912138 |
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Author | : Sergio J. Rojas G. |
Publisher | : Packt Publishing Ltd |
Total Pages | : 188 |
Release | : 2015-02-26 |
Genre | : Computers |
ISBN | : 1783987715 |
This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.
Author | : V Kishore Ayyadevara |
Publisher | : Packt Publishing Ltd |
Total Pages | : 381 |
Release | : 2017-12-20 |
Genre | : Computers |
ISBN | : 1788295811 |
Tackle the most sophisticated problems associated with scientific computing and data manipulation using SciPy Key Features Covers a wide range of data science tasks using SciPy, NumPy, pandas, and matplotlib Effective recipes on advanced scientific computations, statistics, data wrangling, data visualization, and more A must-have book if you're looking to solve your data-related problems using SciPy, on-the-go Book Description With the SciPy Stack, you get the power to effectively process, manipulate, and visualize your data using the popular Python language. Utilizing SciPy correctly can sometimes be a very tricky proposition. This book provides the right techniques so you can use SciPy to perform different data science tasks with ease. This book includes hands-on recipes for using the different components of the SciPy Stack such as NumPy, SciPy, matplotlib, and pandas, among others. You will use these libraries to solve real-world problems in linear algebra, numerical analysis, data visualization, and much more. The recipes included in the book will ensure you get a practical understanding not only of how a particular feature in SciPy Stack works, but also of its application to real-world problems. The independent nature of the recipes also ensure that you can pick up any one and learn about a particular feature of SciPy without reading through the other recipes, thus making the book a very handy and useful guide. What you will learn Get a solid foundation in scientific computing using Python Master common tasks related to SciPy and associated libraries such as NumPy, pandas, and matplotlib Perform mathematical operations such as linear algebra and work with the statistical and probability functions in SciPy Master advanced computing such as Discrete Fourier Transform and K-means with the SciPy Stack Implement data wrangling tasks efficiently using pandas Visualize your data through various graphs and charts using matplotlib Who this book is for Python developers, aspiring data scientists, and analysts who want to get started with scientific computing using Python will find this book an indispensable resource. If you want to learn how to manipulate and visualize your data using the SciPy Stack, this book will also help you. A basic understanding of Python programming is all you need to get started.
Author | : Cyrille Rossant |
Publisher | : Packt Publishing Ltd |
Total Pages | : 899 |
Release | : 2014-09-25 |
Genre | : Computers |
ISBN | : 178328482X |
Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
Author | : Ivan Idris |
Publisher | : Packt Publishing Ltd |
Total Pages | : 254 |
Release | : 2014-06-13 |
Genre | : Computers |
ISBN | : 1783983914 |
A step-by-step guide, packed with examples of practical numerical analysis that will give you a comprehensive, but concise overview of NumPy. This book is for programmers, scientists, or engineers, who have basic Python knowledge and would like to be able to do numerical computations with Python.
Author | : Ivan Idris |
Publisher | : Packt Publishing Ltd |
Total Pages | : 357 |
Release | : 2012-10-25 |
Genre | : Computers |
ISBN | : 1849518939 |
Written in Cookbook style, the code examples will take your Numpy skills to the next level. This book will take Python developers with basic Numpy skills to the next level through some practical recipes.