Key Features
Book Description
What you will learn
- Install NumPy, matplotlib, SciPy, and IPython on various operating systems
- Use NumPy array objects to perform array operations
- Familiarize yourself with commonly used NumPy functions
- Use NumPy matrices for matrix algebra
- Work with the NumPy modules to perform various algebraic operations
- Test NumPy code with the numpy.testing module
- Plot simple plots, subplots, histograms, and more with matplotlib
Who this book is for
This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.
Table of Contents
- NumPy and Python Quick Start
- Beginning with NumPy Fundamentals
- Understanding Commonly Used Functions
- Convenience Functions for Your Convenience
- Working with Matrices and ufuncs
- Moving Further with NumPy Modules
- Peeking into Special Routines
- Assuring Quality with Testing
- Plotting with Matplotlib
- When NumPy is Not Enough ? SciPy and Beyond
- Playing with Pygame
- Appendix A
- Appendix B
- Appendix C
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