Index

A

• adjusted autoregressive model
  • setting up / The time-dependent temperature mean adjusted autoregressive model
• ARMA model
  • about / Forecasting with an ARMA model
  • used, for forecasting / Forecasting with an ARMA model
• array() function / Creating a multidimensional array
• array shapes, NumPy
  • manipulating / Manipulating array shapes
  • arrays, flattening / Manipulating array shapes
  • arrays, stacking / Stacking arrays
  • arrays, splitting / Splitting arrays
  • array attributes / Array attributes
  • arrays, converting / Converting arrays
• assert functions, NumPy
  • about / Assert functions
  • assert_almost_equal function / The assert_almost_equal function
  • assert_approx_equal function / Approximately equal arrays
  • assert_array_almost_equal function / The assert_array_almost_equal function
• assert_almost_equal function / Assert functions, The assert_almost_equal function
• assert_approx_equal function / Assert functions, Approximately equal arrays
• assert_array_almost_equal function / Assert functions
  • about / The assert_array_almost_equal function
• assert_array_equal function / Assert functions
• assert_array_less function / Assert functions
• assert_equal function / Assert functions
• assert_raises function / Assert functions
• assert_string_equal function / Assert functions
• assert_warns function / Assert functions
• atmospheric humidity
  • about / Analyzing atmospheric humidity in De Bilt
• atmospheric humidity, KNMI De Bilt data
  • analyzing / Analyzing atmospheric humidity in De Bilt
• atmospheric pressure
  • about / Analyzing atmospheric pressure in De Bilt
• atmospheric pressure, KNMI De Bilt data file
  • analyzing / Analyzing atmospheric pressure in De Bilt
• Augmented Dickey Fuller (ADF) test / Demonstrating cointegration
• Autoregressive (AR) model
  • about / The Autoregressive Moving Average temperature model
• Autoregressive Moving Average (ARMA) model
  • about / The Autoregressive Moving Average temperature model
• average De Bilt temperature
  • outliers analysis / Outliers analysis of average De Bilt temperature
• average temperature autocorrelation
  • examining, with pandas / Examining autocorrelation of average temperature with pandas

B

• basic data analysis
  • dataset / Introducing the dataset
• Blaze
  • NumPy, comparing with / Comparing NumPy to Blaze
  • about / Comparing NumPy to Blaze
  • URL / Comparing NumPy to Blaze
• Boolean indexing
  • about / Indexing arrays with Booleans
  • performing / Indexing arrays with Booleans

C

• character codes
  • about / Character codes
• clustering
  • about / Clustering stocks with scikit-learn
• cointegration
  • about / Demonstrating cointegration
  • demonstrating / Demonstrating cointegration
• column stacking, NumPy arrays
  • about / Stacking arrays
• column_stack() function / Stacking arrays
• concatenate() function / Stacking arrays
• corner detection
  • about / Detecting corners
  • performing / Detecting corners
• Cython
  • about / Using Cython with NumPy
  • using, with NumPy / Using Cython with NumPy

D

• daily temperature range, KNMI De Bilt data file
  • about / Determining the daily temperature range
  • determining / Determining the daily temperature range
• data analysis, KNMI weather station
  • daily temperature range, determining / Determining the daily temperature range
  • yearly average temperature, determining / Looking for evidence of global warming
  • solar radiation, comparing with temperature / Comparing solar radiation versus temperature
  • wind direction, analyzing / Analyzing wind direction
  • wind speed, analyzing / Analyzing wind speed
  • precipitation, analyzing / Analyzing precipitation and sunshine duration
  • sunshine duration, analyzing / Analyzing precipitation and sunshine duration
  • De Bilt precipitation data, analyzing / Analyzing monthly precipitation in De Bilt
  • De Bilt atmospheric pressure, analyzing / Analyzing atmospheric pressure in De Bilt
  • De Bilt atmospheric humidity, analyzing / Analyzing atmospheric humidity in De Bilt
• data type objects
  • about / Data type objects
• day-of-the-year temperature model
  • about / Introducing the day-of-the-year temperature model
  • used, for modeling temperature / Day-of-year temperature take two
• debugging
  • about / Debugging with IPython
  • IPython, used / Debugging with IPython
• decorators
  • applying / Nose tests decorators
• deprecated decorator / Nose tests decorators
• depth-wise splitting, NumPy arrays
  • about / Splitting arrays
• depth stacking, NumPy arrays
  • about / Stacking arrays
• Dow Jones Industrial (DJI)
  • about / Clustering stocks with scikit-learn
• dsplit() function
  • about / Splitting arrays
• dtype attributes
  • about / dtype attributes
• dtype constructors
  • about / dtype constructors

E

• Empirical Mode Decomposition (EMD) / Introducing the Sunspot data

F

• fancy indexing
  • about / Fancy indexing
  • performing / Fancy indexing
• filter
  • designing / Designing the filter
• flat attribute, ndarray / Array attributes
• flatten() function
  • about / Manipulating array shapes
• forecasting
  • ARMA model, used / Forecasting with an ARMA model

G

• Gaussian integral / Numerical integration

H

• horizontal splitting, NumPy arrays
  • about / Splitting arrays
• horizontal stacking, NumPy arrays
  • about / Stacking arrays

I

• iirdesign function / Filtering a signal
• imag attribute, ndarray / Array attributes
• inter-quartile range / Outliers analysis of average De Bilt temperature
• interp1d class / Interpolation
• interpolation
  • about / Interpolation
• intra-year daily average temperatures
  • analysing / Analyzing intra-year daily average temperatures
• Intrinsic Mode Functions (IMF)
  • about / Introducing the Sunspot data
  • extracting, via sifting / Introducing the Sunspot data
• IPython
  • installing, on Windows / Installing NumPy, Matplotlib, SciPy, and IPython on Windows
  • installing, on Linux / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • program, profiling with / Profiling a program with IPython
  • about / Profiling a program with IPython
  • debugging with / Debugging with IPython
• itemsize attribute, ndarray / Array attributes
• ix_() function
  • about / Indexing with a list of locations

K

• KNMI
  • URL / Introducing the dataset
  • about / Introducing the dataset
• knownfailureif decorator / Nose tests decorators

L

• linear combination
  • about / Forecasting with an ARMA model
• Linux
  • NumPy, installing / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • Matplotlib, installing / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • SciPy, installing / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • IPython, installing / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
• Linux distributions
  • Arch Linux / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • Debian / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • Fedora / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • Gentoo / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • OpenSUSE / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • Slackware / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
• loadtxt function
  • about / Introducing the dataset

M

• Mac OS X
  • NumPy, installing / Installing NumPy, Matplotlib, and SciPy on Mac OS X
  • Matplotlib, installing / Installing NumPy, Matplotlib, and SciPy on Mac OS X
  • SciPy, installing / Installing NumPy, Matplotlib, and SciPy on Mac OS X
• Matplotlib
  • installing, on Windows / Installing NumPy, Matplotlib, SciPy, and IPython on Windows
  • installing, on Linux / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • installing, on Mac OS X / Installing NumPy, Matplotlib, and SciPy on Mac OS X
• monthly precipitation, KNMI De Bilt data file
  • analyzing / Analyzing monthly precipitation in De Bilt
• Moving Average (MA) model
  • about / The Autoregressive Moving Average temperature model
• moving averages
  • about / Moving averages
  • ploting / Moving averages
• moving average temperature model
  • about / Moving-average temperature model with lag 1
• multidimensional NumPy array
  • creating / Creating a multidimensional array

N

• nbytes attribute, ndarray / Array attributes
• ndarray
  • about / The NumPy array object
  • ndim attribute / Array attributes
  • size attribute / Array attributes
  • itemsize attribute / Array attributes
  • nbytes attribute / Array attributes
  • T attribute / Array attributes
  • real attribute / Array attributes
  • imag attribute / Array attributes
  • flat attribute / Array attributes
• ndim attribute, ndarray / Array attributes
• nose
  • about / Nose tests decorators
  • decorators, using / Nose tests decorators
  • installing / Nose tests decorators
• Not a Number (NaN)
  • about / Introducing the dataset
• numerical integration
  • about / Numerical integration
• NumPy
  • about / Python
  • installing, on Windows / Installing NumPy, Matplotlib, SciPy, and IPython on Windows
  • installing, on Linux / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • installing, on Mac OS X / Installing NumPy, Matplotlib, and SciPy on Mac OS X
  • building, from source / Building from source
  • online resources / Online resources and help
  • forum link / Online resources and help
  • assert functions / Assert functions
  • Cython, using with / Using Cython with NumPy
  • comparing, to Blaze / Comparing NumPy to Blaze
• numpy.testing module
  • decorators / Nose tests decorators
• NumPy array object
  • about / The NumPy array object
• NumPy arrays
  • about / NumPy arrays
  • adding / Adding arrays
  • advantages / The advantages of using NumPy arrays
  • array elements, selecting / Selecting array elements
  • record data type, creating / Creating a record data type
  • one-dimensional, slicing / One-dimensional slicing and indexing
  • one-dimensional, indexing / One-dimensional slicing and indexing
  • converting / Converting arrays
  • views, creating / Creating views and copies
  • fancy indexing / Fancy indexing
  • indexing, performing with list of locations / Indexing with a list of locations
  • indexing, with Booleans / Indexing arrays with Booleans
  • stride tricks, applying for Sudoku / Stride tricks for Sudoku
  • broadcasting / Broadcasting arrays
• NumPy basics
  • NumPy array object / The NumPy array object
• NumPy numerical types
  • overview / NumPy numerical types
  • bool / NumPy numerical types
  • inti / NumPy numerical types
  • int8 / NumPy numerical types
  • int16 / NumPy numerical types
  • int32 / NumPy numerical types
  • int64 / NumPy numerical types
  • uint8 / NumPy numerical types
  • uint16 / NumPy numerical types
  • uint32 / NumPy numerical types
  • uint64 / NumPy numerical types
  • float16 / NumPy numerical types
  • float32 / NumPy numerical types
  • float64 / NumPy numerical types
  • complex64 / NumPy numerical types
  • complex / NumPy numerical types
  • complex128 / NumPy numerical types
  • data type objects / Data type objects
  • character codes / Character codes
  • dtype constructors / dtype constructors
  • dtype attributes / dtype attributes

O

• one-dimensional NumPy arrays
  • slicing / One-dimensional slicing and indexing
  • indexing / One-dimensional slicing and indexing
• outliers analysis, average De Bilt temperature
  • performing / Outliers analysis of average De Bilt temperature

P

• pandas DataFrame
  • used, for descriptive statistics / Describing data with pandas DataFrames
• pandas library
  • about / Examining autocorrelation of average temperature with pandas
  • used, for examining average temperature autocorrelation / Examining autocorrelation of average temperature with pandas
  • used, for correlating weather and stocks / Correlating weather and stocks with pandas
• precipitation, KNMI De Bilt data file
  • analyzing / Analyzing precipitation and sunshine duration
• predictive analytics
  • average temperature autocorrelation, examining with pandas / Examining autocorrelation of average temperature with pandas
  • data, describing with pandas DataFrames / Describing data with pandas DataFrames
  • weather and stocks, correlating with pandas / Correlating weather and stocks with pandas
  • temperature, predicting / Predicting temperature
  • intra-year daily average temperatures, analysing / Analyzing intra-year daily average temperatures
  • day-of-the-year temperature model / Introducing the day-of-the-year temperature model
  • temperature, modeling with SciPy leastsq function / Modeling temperature with the SciPy leastsq function
  • day-of-the-year temperature / Day-of-year temperature take two
  • moving average temperature model / Moving-average temperature model with lag 1
• program
  • profiling, with IPython / Profiling a program with IPython
• Python
  • about / Python
• PyUnit API
  • about / Performing Unit tests

Q

• quad function / Numerical integration

R

• ravel() function
  • about / Manipulating array shapes
• real attribute, ndarray / Array attributes
• record data type
  • about / Creating a record data type
  • creating / Creating a record data type
• resize() method
  • about / Manipulating array shapes
• robust statistics / Using more robust statistics
• row stacking, NumPy arrays
  • about / Stacking arrays

S

• #scipy channel / Online resources and help
• scikit-learn
  • about / Clustering stocks with scikit-learn
  • used, for clustering stocks / Clustering stocks with scikit-learn
• SciPy
  • installing, on Windows / Installing NumPy, Matplotlib, SciPy, and IPython on Windows
  • installing, on Linux / Installing NumPy, Matplotlib, SciPy, and IPython on Linux
  • installing, on Mac OS X / Installing NumPy, Matplotlib, and SciPy on Mac OS X
  • online resources / Online resources and help
  • forum link / Online resources and help
• scipy.integrate / Numerical integration
• scipy.interpolate function / Interpolation
• SciPy leastsq function
  • used, for modeling temperature / Modeling temperature with the SciPy leastsq function
• setastest decorator / Nose tests decorators
• shape() function
  • about / Manipulating array shapes
• sifting process
  • about / Introducing the Sunspot data
  • steps / Sifting continued
• signal
  • filtering / Filtering a signal
• signal processing techniques
  • Sunspot data / Introducing the Sunspot data
  • moving averages / Moving averages
• size attribute, ndarray / Array attributes
• skipif decorator / Nose tests decorators
• slow decorator / Nose tests decorators
• smoothing
  • about / Smoothing functions
• smoothing functions
  • about / Smoothing functions
• solar radiation
  • comparing, with temperature / Comparing solar radiation versus temperature
• split() function
  • about / Splitting arrays
• splitting, NumPy arrays
  • performing / Splitting arrays
  • horizontal splitting / Splitting arrays
  • vertical splitting / Splitting arrays
  • depth-wise splitting / Splitting arrays
• stacking, NumPy arrays
  • performing / Stacking arrays
  • horizontal stacking / Stacking arrays
  • vertical stacking / Stacking arrays
  • depth stacking / Stacking arrays
  • column stacking / Stacking arrays
  • row stacking / Stacking arrays
• stocks
  • clustering, with scikit-learn / Clustering stocks with scikit-learn
• stride tricks
  • applying, to Sudoku / Stride tricks for Sudoku
• sunshine duration, KNMI De Bilt data file
  • analyzing / Analyzing precipitation and sunshine duration
• sunspot data
  • about / Introducing the Sunspot data
• sunspots
  • about / Introducing the Sunspot data

T

• T attribute, ndarray / Array attributes
• temperature
  • predicting / Predicting temperature
  • autoregressive model with lag 1 / Autoregressive model with lag 1
  • autoregressive model with lag 2 / Autoregressive model with lag 2
  • modeling, with SciPy leastsq function / Modeling temperature with the SciPy leastsq function
• transpose() function
  • about / Manipulating array shapes

U

• unit tests
  • performing / Performing Unit tests

V

• vertical splitting, NumPy arrays
  • about / Splitting arrays
• vertical stacking, NumPy arrays
  • about / Stacking arrays
• views, NumPy arrays
  • creating / Creating views and copies
• vsplit() function
  • about / Splitting arrays

W

• weather and stocks
  • correlating, with pandas / Correlating weather and stocks with pandas
• wind direction, KNMI De Bilt data file
  • analyzing / Analyzing wind direction
• Windows
  • NumPy, installing / Installing NumPy, Matplotlib, SciPy, and IPython on Windows
  • IPython, installing / Installing NumPy, Matplotlib, SciPy, and IPython on Windows
  • SciPy, installing / Installing NumPy, Matplotlib, SciPy, and IPython on Windows
  • Matplotlib, installing / Installing NumPy, Matplotlib, SciPy, and IPython on Windows
• wind speed, KNMI De Bilt data file
  • analyzing / Analyzing wind speed

Y

• yearly average temperature, KNMI De Bilt data file
  • determining / Looking for evidence of global warming