- Cover
- Title
- Copyright
- Dedication
- Contents at a Glance
- Contents
- About the Author
- About the Technical Reviewer
- Introduction
- Chapter 1: Introduction to Computing with Python
- Chapter 2: Vectors, Matrices, and Multidimensional Arrays
- 2.1 Importing NumPy
- 2.2 The NumPy Array Object
- 2.3 Creating Arrays
- 2.3.1 Arrays Created from Lists and Other Array-like Objects
- 2.3.2 Arrays Filled with Constant Values
- 2.3.3 Arrays Filled with Incremental Sequences
- 2.3.4 Arrays Filled with Logarithmic Sequences
- 2.3.5 Mesh-grid Arrays
- 2.3.6 Creating Uninitialized Arrays
- 2.3.7 Creating Arrays with Properties of Other Arrays
- 2.3.8 Creating Matrix Arrays
- 2.4 Indexing and Slicing
- 2.5 Reshaping and Resizing
- 2.6 Vectorized Expressions
- 2.7 Matrix and Vector Operations
- 2.8 Summary
- 2.9 Further Reading
- 2.10 References
- Chapter 3: Symbolic Computing
- Chapter 4: Plotting and Visualization
- Chapter 5: Equation Solving
- Chapter 6: Optimization
- Chapter 7: Interpolation
- Chapter 8: Integration
- Chapter 9: Ordinary Differential Equations
- Chapter 10: Sparse Matrices and Graphs
- Chapter 11: Partial Differential Equations
- Chapter 12: Data Processing and Analysis
- Chapter 13: Statistics
- Chapter 14: Statistical Modeling
- Chapter 15: Machine Learning
- Chapter 16: Bayesian Statistics
- Chapter 17: Signal Processing
- Chapter 18: Data Input and Output
- Chapter 19: Code Optimization
- Appendix A Installation
- Index
Numerical Python
A Practical Techniques Approach for Industry
Robert Johansson
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