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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

  Attributes

  d | int | number of dimensions
  n | int | number of datapoints

  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
  kde.resample(size=None) | array | randomly sample a dataset from the estimated pdf.

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