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# scipy.stats.gaussian_kde

class `scipy.stats.``gaussian_kde`(dataset)

  Representation of a kernel-density estimate using Gaussian kernels.

  Parameters: | dataset : (# of dims, # of data)-array datapoints to estimate from
  Methods: | kde.evaluate(points) : array evaluate the estimated pdf on a provided set of points kde(points) : array same as kde.evaluate(points) kde.integrate_gaussian(mean, cov) : float multiply pdf with a specified Gaussian and integrate over the whole domain kde.integrate_box_1d(low, high) : float integrate pdf (1D only) between two bounds kde.integrate_box(low_bounds, high_bounds) : float integrate pdf over a rectangular space between low_bounds and high_bounds kde.integrate_kde(other_kde) : float integrate two kernel density estimates multiplied together

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