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Python Data Analysis by Ivan Idris

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SciPy

This section shows useful SciPy functions:

scipy.fftpack

  • fftshift(x, axes=None): This function shifts the zero-frequency component to the center of the spectrum
  • rfft(x, n=None, axis=-1, overwrite_x=0): This function performs a discrete Fourier transform of an array containing real values

scipy.signal

  • detrend(data, axis=-1, type='linear', bp=0): This function removes the linear trend or a constant from the data
  • medfilt(volume, kernel_size=None): This function applies a median filter on an array
  • wiener(im, mysize=None, noise=None): This function applies a Wiener filter on an array

scipy.stats

  • anderson(x, dist='norm'): This function performs the Anderson-Darling test for data coming from a specified distribution
  • kruskal(*args): This function performs ...

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