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NumPy Beginner's Guide Second Edition
Table of Contents
Numpy Beginner's Guide Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers and more
Why Subscribe?
Free Access for Packt account holders
Preface
What is NumPy?
History
Why use NumPy?
Limitations of NumPy
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. NumPy Quick Start
Python
Time for action – installing Python on different operating systems
What just happened?
Windows
Time for action – installing NumPy, Matplotlib, SciPy, and IPython on Windows
What just happened?
Linux
Time for action – installing NumPy, Matplotlib, SciPy, and IPython on Linux
What just happened?
Mac OS X
Time for action – installing NumPy, Matplotlib, and SciPy on Mac OS X
What just happened?
Time for action – installing NumPy, SciPy, Matplotlib, and IPython with MacPorts or Fink
What just happened?
Building from source
Arrays
Time for action – adding vectors
What just happened?
Pop quiz Functioning of the arange function
Have a go hero – continue the analysis
IPython—an interactive shell
Online resources and help
Summary
2. Beginning with NumPy Fundamentals
NumPy array object
Time for action – creating a multidimensional array
What just happened?
Pop quiz – the shape of ndarray
Have a go hero – create a three-by-three matrix
Selecting elements
NumPy numerical types
Data type objects
Character codes
dtype constructors
dtype attributes
Time for action – creating a record data type
What just happened?
One-dimensional slicing and indexing
Time for action – slicing and indexing multidimensional arrays
What just happened?
Time for action – manipulating array shapes
What just happened?
Stacking
Time for action – stacking arrays
What just happened?
Splitting
Time for action – splitting arrays
What just happened?
Array attributes
Time for action – converting arrays
What just happened?
Summary
3. Get in Terms with Commonly Used Functions
File I/O
Time for action – reading and writing files
What just happened?
CSV files
Time for action – loading from CSV files
What just happened?
Volume-weighted average price
Time for action – calculating volume-weighted average price
What just happened?
The mean function
Time-weighted average price
Pop quiz – computing the weighted average
Have a go hero – calculating other averages
Value range
Time for action – finding highest and lowest values
What just happened?
Statistics
Time for action – doing simple statistics
What just happened?
Stock returns
Time for action – analyzing stock returns
What just happened?
Dates
Time for action – dealing with dates
What just happened?
Have a go hero – looking at VWAP and TWAP
Weekly summary
Time for action – summarizing data
What just happened?
Have a go hero – improving the code
Average true range
Time for action – calculating the average true range
What just happened?
Have a go hero – taking the minimum function for a spin
Simple moving average
Time for action – computing the simple moving average
What just happened?
Exponential moving average
Time for action – calculating the exponential moving average
What just happened?
Bollinger bands
Time for action – enveloping with Bollinger bands
What just happened?
Have a go hero – switching to exponential moving average
Linear model
Time for action – predicting price with a linear model
What just happened?
Trend lines
Time for action – drawing trend lines
What just happened?
Methods of ndarray
Time for action – clipping and compressing arrays
What just happened?
Factorial
Time for action – calculating the factorial
What just happened?
Summary
4. Convenience Functions for Your Convenience
Correlation
Time for action – trading correlated pairs
What just happened?
Pop quiz – calculating covariance
Polynomials
Time for action – fitting to polynomials
What just happened?
Have a go hero – improving the fit
On-balance volume
Time for action – balancing volume
What just happened?
Simulation
Time for action – avoiding loops with vectorize
What just happened?
Have a go hero – analyzing consecutive wins and losses
Smoothing
Time for action – smoothing with the hanning function
What just happened?
Have a go hero – smoothing variations
Summary
5. Working with Matrices and ufuncs
Matrices
Time for action – creating matrices
What just happened?
Creating a matrix from other matrices
Time for action – creating a matrix from other matrices
What just happened?
Pop quiz – defining a matrix with a string
Universal functions
Time for action – creating universal function
What just happened?
Universal function methods
Time for action – applying the ufunc methods on add
What just happened?
Arithmetic functions
Time for action – dividing arrays
What just happened?
Have a go hero – experimenting with __future__.division
Modulo operation
Time for action – computing the modulo
What just happened?
Fibonacci numbers
Time for action – computing Fibonacci numbers
What just happened?
Have a go hero – timing the calculations
Lissajous curves
Time for action – drawing Lissajous curves
What just happened?
Square waves
Time for action – drawing a square wave
What just happened?
Have a go hero – getting rid of the loop
Sawtooth and triangle waves
Time for action – drawing sawtooth and triangle waves
What just happened?
Have a go hero – getting rid of the loop
Bitwise and comparison functions
Time for action – twiddling bits
What just happened?
Summary
6. Move Further with NumPy Modules
Linear algebra
Time for action – inverting matrices
What just happened?
Pop quiz – creating a matrix
Have a go hero – inverting your own matrix
Solving linear systems
Time for action – solving a linear system
What just happened?
Finding eigenvalues and eigenvectors
Time for action – determining eigenvalues and eigenvectors
What just happened?
Singular value decomposition
Time for action – decomposing a matrix
What just happened?
Pseudoinverse
Time for action – computing the pseudo inverse of a matrix
What just happened?
Determinants
Time for action – calculating the determinant of a matrix
What just happened?
Fast Fourier transform
Time for action – calculating the Fourier transform
What just happened?
Shifting
Time for action – shifting frequencies
What just happened?
Random numbers
Time for action – gambling with the binomial
What just happened?
Hypergeometric distribution
Time for action – simulating a game show
What just happened?
Continuous distributions
Time for action – drawing a normal distribution
What just happened?
Lognormal distribution
Time for action – drawing the lognormal distribution
What just happened?
Summary
7. Peeking into Special Routines
Sorting
Time for action – sorting lexically
What just happened?
Have a go hero – trying a different sort order
Complex numbers
Time for action – sorting complex numbers
What just happened?
Pop quiz – generating random numbers
Searching
Time for action – using searchsorted
What just happened?
Array elements' extraction
Time for action – extracting elements from an array
What just happened?
Financial functions
Time for action – determining future value
What just happened?
Present value
Time for action – getting the present value
What just happened?
Net present value
Time for action – calculating the net present value
What just happened?
Internal rate of return
Time for action – determining the internal rate of return
What just happened?
Periodic payments
Time for action – calculating the periodic payments
What just happened?
Number of payments
Time for action – determining the number of periodic payments
What just happened?
Interest rate
Time for action – figuring out the rate
What just happened?
Window functions
Time for action – plotting the Bartlett window
What just happened?
Blackman window
Time for action – smoothing stock prices with the Blackman window
What just happened?
Hamming window
Time for action – plotting the Hamming window
What just happened?
Kaiser window
Time for action – plotting the Kaiser window
What just happened?
Special mathematical functions
Time for action – plotting the modified Bessel function
What just happened?
sinc
Time for action – plotting the sinc function
What just happened?
Summary
8. Assure Quality with Testing
Assert functions
Time for action – asserting almost equal
What just happened?
Pop quiz – specifying decimal precision
Approximately equal arrays
Time for action – asserting approximately equal
What just happened?
Almost equal arrays
Time for action – asserting arrays almost equal
What just happened?
Have a go hero – comparing array with different shapes
Equal arrays
Time for action – comparing arrays
What just happened?
Ordering arrays
Time for action – checking the array order
What just happened?
Objects comparison
Time for action – comparing objects
What just happened?
String comparison
Time for action – comparing strings
What just happened?
Floating point comparisons
Time for action – comparing with assert_array_almost_equal_nulp
What just happened?
Comparison of floats with more ULPs
Time for action – comparing using maxulp of 2
What just happened?
Unit tests
Time for action – writing a unit test
What just happened?
Nose tests decorators
Time for action – decorating tests
What just happened?
Docstrings
Time for action – executing doctests
What just happened?
Summary
9. Plotting with Matplotlib
Simple plots
Time for action – plotting a polynomial function
What just happened?
Pop quiz – the plot function
Plot format string
Time for action – plotting a polynomial and its derivative
What just happened?
Subplots
Time for action – plotting a polynomial and its derivatives
What just happened?
Finance
Time for action – plotting a year’s worth of stock quotes
What just happened?
Histograms
Time for action – charting stock price distributions
What just happened?
Have a go hero – drawing a bell curve
Logarithmic plots
Time for action – plotting stock volume
What just happened?
Scatter plots
Time for action – plotting price and volume returns with scatter plot
What just happened?
Fill between
Time for action – shading plot regions based on a condition
What just happened?
Legend and annotations
Time for action – using legend and annotations
What just happened?
Three dimensional plots
Time for action – plotting in three dimensions
What just happened?
Contour plots
Time for action – drawing a filled contour plot
What just happened?
Animation
Time for action – animating plots
What just happened?
Summary
10. When NumPy is Not Enough – SciPy and Beyond
MATLAB and Octave
Time for action – saving and loading a .mat file
What just happened?
Pop quiz – loading .mat files
Statistics
Time for action – analyzing random values
What just happened?
Have a go hero – improving the data generation
Samples’ comparison and SciKits
Time for action – comparing stock log returns
What just happened?
Signal processing
Time for action – detecting a trend in QQQ
What just happened?
Fourier analysis
Time for action – filtering a detrended signal
What just happened?
Mathematical optimization
Time for action – fitting to a sine
What just happened?
Numerical integration
Time for action – calculating the Gaussian integral
What just happened?
Interpolation
Time for action – interpolating in one dimension
What just happened?
Image processing
Time for action – manipulating Lena
What just happened?
Audio processing
Time for action – replaying audio clips
What just happened?
Summary
11. Playing with Pygame
Pygame
Time for action – installing Pygame
Hello World
Time for action – creating a simple game
What just happened?
Animation
Time for action – animating objects with NumPy and Pygame
What just happened?
Matplotlib
Time for action – using Matplotlib in Pygame
What just happened?
Surface pixels
Time for action – accessing surface pixel data with NumPy
What just happened?
Artificial intelligence
Time for action – clustering points
What just happened?
OpenGL and Pygame
Time for action – drawing the Sierpinski gasket
What just happened?
Simulation game with PyGame
Time for action – simulating life
What just happened?
Summary
A. Pop Quiz Answers
Chapter 1, NumPy Quick Start
Chapter 2, Beginning with NumPy Fundamentals
Chapter 3, Get into Terms with Commonly Used Functions
Chapter 4, Convenience functions for your convenience
Chapter 5, Working with Matrices and ufuncs
Chapter 6, Move further with NumPy modules
Chapter 7, Peeking into special routines
Chapter 8, Assure Quality with Testing
Chapter 9, Plotting with Matplotlib
Chapter 10, When NumPy is not enough Scipy and beyond
Index
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