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Chapter 1: Introduction
Chapter 2: The Core Python Language I
Examples
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Additional Problems
Chapter 3: Simple Plotting with pylab
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Chapter 4: The core Python language II
Examples
Questions
Problems
Additional Problems
Chapter 5: IPython and IPython Notebook
Examples
Chapter 6: NumPy
Examples
Questions
Problems
Additional Examples
Additional Problems
Chapter 7: Matplotlib
Examples
Questions
Problems
Chapter 8: SciPy
Examples
Questions
Problems
Additional Examples
Additional Problems
Chapter 9: General Scientific Programming
Examples
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Problems
Errata
Book (2nd ed.)
Chapter 1: Introduction
Chapter 2: The Core Python Language I
Examples
Questions
Problems
Additional Problems
Chapter 3: Simple Plots and Charts
Examples
Problems
Chapter 4: The core Python language II
Examples
Questions
Problems
Additional Problems
Chapter 5: IPython and Jupyter Notebook
Examples
Problems
Chapter 6: NumPy
Examples
Questions
Problems
Additional Examples
Additional Problems
Chapter 7: Matplotlib
Examples
Questions
Problems
Chapter 8: SciPy
Examples
Questions
Problems
Additional Examples
Additional Problems
Chapter 9: Data Analysis with pandas
Examples
Problems
Chapter 10: General Scientific Programming
Examples
Questions
Problems
Errata
Additional Notes
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Chapter 6: NumPy
Chapter 6: NumPy
Examples
E6.1 A "comb" function
E6.2 Creating a Magic Square
E6.3 vstack and hstack
E6.4 Checking a Sudoku grid for validity
E6.5 argmax and argmin
E6.6 Using NumPy's loadtxt method
E6.7 The Stroop effect
E6.8 Covariance with np.cov
E6.9 The correlation between air pressure and temperature
E6.10 The height of liquid in a spherical tank
E6.11 Finding a best-fit straight line
E6.12 Fitting the Beer-Lambert law with NumPy
E6.13 Creating a rotation matrix in NumPy
E6.14 Matrix operations
E6.15 Mesh analysis of a electrical network
E6.16 Random sampling of evenly-spaced real numbers
E6.17 Simulating coin-tosses
E6.18 The normal distribution
E6.19 Modelling the distribution of $\mathrm{^{13}C}$ atoms in $\mathrm{C_{60}}$
E6.20 The probability of cleaving DNA with EcoRI
E6.21 Blurring an image with a two-dimensional FFT
Questions
Q6.1.1 np.ndarray and np.array
Q6.1.2 Creating a NumPy array #1
Q6.1.3 Creating a NumPy array #2
Q6.1.4 Changing the data type of an array
Q6.1.5 Indexing and slicing a NumPy array
Q6.1.6 Boolean indexing
Q6.1.7 Using np.isclose #1
Q6.1.8 Using np.isclose #2
Q6.1.9 Verifying a magic square
Q6.1.10 Determining if an array is monotonically increasing
Q6.1.11 The dtypes of scalars and arrays
Q6.4.1 Derivative of a polynomial
Q6.4.2 Classifying the stationary points of a polynomial
Q6.5.1 The unitary property of the Pauli matrices
Q6.5.2 Fitting data to a quadratic function
Q6.7.1 Using np.random.randint
Q6.7.2 Using np.random.randint to sample from a set of evenly-spaced reals
Q6.7.3 The Mega Millions lottery
Q6.7.4 Probability of misprints
Q6.8.1 Direct implementation of the discrete Fourier Transform
Problems
P6.1
P6.1.1 A structured array of whale species data
P6.1.2 The shoelace algorithm
P6.1.3 Gaussian functions and their derivatives
P6.2
P6.2.1 8000 m peaks
P6.2.2 Airport distances
P6.2.3 Immunization rates
None Analysing meteorological data with NumPy
P6.3
P6.3.1 Analysing lottery results
P6.3.2 Plotting a histogram with pylab.bar
P6.3.3 Plotting a height distribution histogram
P6.4
P6.4.1 Analysis of a nuclear explosion
P6.4.2 Linear Regression on four data sets
P6.4.3 The van der Waals equation of state
P6.4.4 Saturn V first stage launch analysis
P6.5
P6.5.1 Planck units of measurement
P6.5.2 The moment of inertia tensor
P6.5.3 Singular value decomposition
Measuring the Coefficient of Restitution
P6.6
P6.6.1 Finding the number of integers not containing the digit 5
P6.6.2 The Fibonacci sequence by matrix similarity transform
P6.6.3 Conic sections
P6.7
P6.7.1 Coin-flipping simulation
P6.7.2 Buffon's needle
P6.7.3 A simple model for chemotaxis
P6.7.4 Modeling meanders
P6.8
P6.8.1 Apodization
P6.8.2 Fourier expansion of a square wave
P6.8.3 Fourier transform of a sound file
Additional Examples
$k$-means clustering
Additional Problems
The Gibbs phenomenon
Analysing Snakes and Ladders as a Markov Chain
Structure factors for perfect crystals
The temperature dependence of resistivity