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# scipy.stats.relfreq

`scipy.stats.``relfreq`(a, numbins=10, defaultreallimits=None, weights=None)

  Returns a relative frequency histogram, using the histogram function.

  Parameters : | a : array_like Input array. numbins: int, optional : The number of bins to use for the histogram. Default is 10. defaultlimits: tuple (lower, upper), optional : The lower and upper values for the range of the histogram. If no value is given, a range slightly larger then the range of the values in a is used. Specifically `(a.min() - s, a.max() + s)`, where `s = (1/2)(a.max() - a.min()) / (numbins - 1)`. weights: array_like, optional : The weights for each value in a. Default is None, which gives each value a weight of 1.0
  Returns : | relfreq : ndarray Binned values of relative frequency. lowerreallimit : float Lower real limit binsize : float Width of each bin. extrapoints : int Extra points.

  Examples

      >>> a = np.array([1, 4, 2, 1, 3, 1])
      >>> relfreqs, lowlim, binsize, extrapoints = sp.stats.relfreq(a, numbins=4)
      >>> relfreqs
      array([ 0.5       ,  0.16666667,  0.16666667,  0.16666667])
      >>> np.sum(relfreqs)  # relative frequencies should add up to 1
      0.99999999999999989

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