Numpy Beginner's Guide Second Edition
Time for action – installing Python on different operating systems
Time for action – installing NumPy, Matplotlib, SciPy, and IPython on Windows
Time for action – installing NumPy, Matplotlib, SciPy, and IPython on Linux
Time for action – installing NumPy, Matplotlib, and SciPy on Mac OS X
Time for action – installing NumPy, SciPy, Matplotlib, and IPython with MacPorts or Fink
Time for action – adding vectors
Beginning with NumPy Fundamentals
Time for action – creating a multidimensional array
Time for action – creating a record data type
One-dimensional slicing and indexing
Time for action – slicing and indexing multidimensional arrays
Time for action – manipulating array shapes
Time for action – stacking arrays
Time for action – splitting arrays
Time for action – converting arrays
Get in Terms with Commonly Used Functions
Time for action – reading and writing files
Time for action – loading from CSV files
Time for action – calculating volume-weighted average price
Time for action – finding highest and lowest values
Time for action – doing simple statistics
Time for action – analyzing stock returns
Time for action – dealing with dates
Time for action – summarizing data
Time for action – calculating the average true range
Time for action – computing the simple moving average
Time for action – calculating the exponential moving average
Time for action – enveloping with Bollinger bands
Time for action – predicting price with a linear model
Time for action – drawing trend lines
Time for action – clipping and compressing arrays
Time for action – calculating the factorial
Convenience Functions for Your Convenience
Time for action – trading correlated pairs
Time for action – fitting to polynomials
Time for action – balancing volume
Time for action – avoiding loops with vectorize
Time for action – smoothing with the hanning function
Working with Matrices and ufuncs
Time for action – creating matrices
Creating a matrix from other matrices
Time for action – creating a matrix from other matrices
Time for action – creating universal function
Time for action – applying the ufunc methods on add
Time for action – dividing arrays
Time for action – computing the modulo
Time for action – computing Fibonacci numbers
Time for action – drawing Lissajous curves
Time for action – drawing a square wave
Time for action – drawing sawtooth and triangle waves
Bitwise and comparison functions
Time for action – twiddling bits
Move Further with NumPy Modules
Time for action – inverting matrices
Time for action – solving a linear system
Finding eigenvalues and eigenvectors
Time for action – determining eigenvalues and eigenvectors
Time for action – decomposing a matrix
Time for action – computing the pseudo inverse of a matrix
Time for action – calculating the determinant of a matrix
Time for action – calculating the Fourier transform
Time for action – shifting frequencies
Time for action – gambling with the binomial
Time for action – simulating a game show
Time for action – drawing a normal distribution
Time for action – drawing the lognormal distribution
Time for action – sorting lexically
Time for action – sorting complex numbers
Time for action – using searchsorted
Time for action – extracting elements from an array
Time for action – determining future value
Time for action – getting the present value
Time for action – calculating the net present value
Time for action – determining the internal rate of return
Time for action – calculating the periodic payments
Time for action – determining the number of periodic payments
Time for action – figuring out the rate
Time for action – plotting the Bartlett window
Time for action – smoothing stock prices with the Blackman window
Time for action – plotting the Hamming window
Time for action – plotting the Kaiser window
Special mathematical functions
Time for action – plotting the modified Bessel function
Time for action – plotting the sinc function
Time for action – asserting almost equal
Time for action – asserting approximately equal
Time for action – asserting arrays almost equal
Time for action – comparing arrays
Time for action – checking the array order
Time for action – comparing objects
Time for action – comparing strings
Time for action – comparing with assert_array_almost_equal_nulp
Comparison of floats with more ULPs
Time for action – comparing using maxulp of 2
Time for action – writing a unit test
Time for action – decorating tests
Time for action – executing doctests
Time for action – plotting a polynomial function
Time for action – plotting a polynomial and its derivative
Time for action – plotting a polynomial and its derivatives
Time for action – plotting a year’s worth of stock quotes
Time for action – charting stock price distributions
Time for action – plotting stock volume
Time for action – plotting price and volume returns with scatter plot
Time for action – shading plot regions based on a condition
Time for action – using legend and annotations
Time for action – plotting in three dimensions
Time for action – drawing a filled contour plot
Time for action – animating plots
When NumPy is Not Enough – SciPy and Beyond
Time for action – saving and loading a .mat file
Time for action – analyzing random values
Samples’ comparison and SciKits
Time for action – comparing stock log returns
Time for action – detecting a trend in QQQ
Time for action – filtering a detrended signal
Time for action – fitting to a sine
Time for action – calculating the Gaussian integral
Time for action – interpolating in one dimension
Time for action – manipulating Lena
Time for action – replaying audio clips
Time for action – installing Pygame
Time for action – creating a simple game
Time for action – animating objects with NumPy and Pygame
Time for action – using Matplotlib in Pygame
Time for action – accessing surface pixel data with NumPy
Time for action – clustering points
Time for action – drawing the Sierpinski gasket