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NumPy 1.5 Beginner's Guide
An action packed guide for the easy-to-use, high performance, free open source NumPy mathematical library using real world examples
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- Cover
- Copyright
- About the Author
- Table of Contents
- Preface
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Chapter 1:
NumPy Quick Start
- Python
- Time for action – installing Python
- Windows
- Time for action – installing NumPy on Windows
- Linux
- Time for action – Installing NumPy on Linux
- Mac OS X
- Time for action – Installing NumPy on Mac OS X
- Building from source
- Time for action –- adding vectors
- IPython_ an interactive shell
- Online Resources and help
- Summary
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Chapter 2:
Beginning with Numpy Fundamentals
- NumPy array object
- + Time for action – creating a matrix
- Selecting elements
- NumPy Numerical Types
- Data Type objects
- Character codes
- Dtype constructors
- Dtype attributes
- Time for action – creating a record data type
- One Dimensional Slicing and indexing
- Time for action – slicing and indexing multi Dimensional arrays
- Time for action – manipulating array shapes
- Stacking
- Time for action – stacking arrays
- Time for action – splitting arrays
- Array attributes
- Time for action – converting arrays
- Summary
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Chapter 3:
Get into terms with commonly
used functions
- File IO
- Time for action – reading and writing files as an example of file
- IO we will create an identity matrix, store its contents in a file,
- read the file contents and print it.
- CSV files
- Time for action – loading from CSV files
- Volume weighted average price
- + Time for action – calculating volume weighted average price
- Value range
- Time for action – finding highest and lowest values
- Statistics
- Time for action – doing simple statistics
- Stock returns
- Time for action – analyzing stock returns
- Dates
- Time for action – dealing with dates
- Weekly summary
- Time for action – summarizing data
- Average True Range
- Time for action – calculating the average true range
- Simple moving average
- Time for action – computing the simplede the window.
- Exponential moving average
- Time for action – calculating the exponential in the weights.
- Bollinger bands
- Time for ction – envelopping with moving average.
- Linear model
- Time for action – predicting price with a linear model
- Trend lines
- Time for action – drawing trend lines
- Methods of ndarray
- Time for action – clipping arrays
- Time for action – compressing arrays
- Factorial
- Time for action – calculating the factorial
- Summary
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Chapter 4:
Convenience Functions for your convenience
- Correlation
- Time for action – trading correlated pairs
- Polynomials
- Time for action – fitting to polynomials
- On balance volume
- Time for action – balancing volume
- The mode
- Time for action – determining the mode of stock returns
- Simulation
- Time for action – avoiding loops with vectorize
- Smoothing
- Time for action – smoothing with the hanning function
- Summary
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Chapter 5:
Working with Matrices and ufuncs
- Matrices
- Time for action – creating matrices
- Matrix from matrices
- Time for action – creating a matrix from other matrices
- Universal functions
- Time for action – creating universal function
- Universal function attributes
- Time for action – reading the attributes of add
- Universal function methods
- Time for action – applying the ufunc methods on add
- Arithmetic functions
- Time for action – dividing arrays
- Modulo operation
- Time for action – computing the modulo
- Fibonacci numbers
- Time for action – computing Fibonacci numbers
- Lissajous curves
- Time for action – drawing Lissajous curves
- Square waves
- Time for action – drawing a square wave
- Sawtooth and triangle waves
- Time for action – drawing sawtooth and triangle waves
- Bitwise and comparison functions
- Time for action – twiddling bits
- Summary
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Chapter 6:
Move further with NumPy Modules
- Linear algebra
- Time for action – inverting matrices
- Solving linear systems
- Time for action – solving a linear system
- Finding eigenvalues and eigenvectors
- Time for action – determining eigenvalues and eigenvectors
- Singular value decomposition
- Time for action – decomposing a matrix
- Pseudo inverse
- Time for action – computing the pseudo inverse of a matrix
- Determinants
- Time for action – calculating the determinant of a matrix
- Fast Fourier transform
- Time for action – calculating the Fourier transform
- Shifting
- Time for action – shifting frequencies
- Random numbers
- Time for action – gambling with the binomial
- Geometric distribution
- Time for action – throwing a dice
- Hypergeometric distribution
- Time for action – simulating a game show
- Continuous distributions
- Time for action – drawing the normal distribution
- Lognormal distribution
- Time for action – drawing the lognormal distribution
- Summary
The book is written in beginner's guide style with each aspect of NumPy demonstrated by real world examples. There is appropriate explained code with the required screenshots thrown in for the novice. This book is for the programmer, scientist or engineer, who has basic Python knowledge and would like to be able to do numerical computations with Python.
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Book Details
Authors
Publishers
Publication year : 2011
License: All rights reserved ©
Times read: 6
