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Guide to NumPy
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  • Title: Guide to NumPy
  • Author(s) Travis E. Oliphant
  • Publisher: Massachusetts Institute of Technology (Dec 7, 2006)
  • License(s): Public Domain Mark 1.0
  • Hardcover/Paperback: N/A
  • eBook: HTML, PDF (371 pages), ePub, Kindle (Mobi), etc.
  • Language: English
  • ISBN-10: N/A
  • ISBN-13: N/A
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Book Description

NumPy is an extension of Python, which provides highly optimized arrays and numerical operations. NumPy replaces a lot of the functionality of Matlab and Mathematica specifically vectorized operations, but in contrast to those products is free and open source. In today's world of science and technology, it is all about speed and flexibility.

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. It will give you a solid foundation in NumPy arrays and universal functions. Learning NumPy Array will help you be productive with NumPy and write clean and fast code.

  • Improve the performance of calculations with clean and efficient NumPy code
  • Analyze large data sets using statistical functions and execute complex linear algebra and mathematical computations
  • Perform complex array operations in a simple manner
About the Authors
  • Travis E. Oliphant is an American data scientist and businessman and 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 numerical and scientific programming. He is the primary developer of the NumPy package and founding contributor to the SciPy package.
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