class_docstr: Laplace distribution.
  
  Parameters
  ----------
  mean : float or array of float (1D or 2D)
      mean of the distribution
  scale : float or array of float (1D or 2D), must be positive
      scale parameter of the distribution, same as standard deviation / sqrt(2)
  index : pd.Index, optional, default = RangeIndex
  columns : pd.Index, optional, default = RangeIndex
  
  Example
  -------
  >>> from sktime.proba.laplace import Laplace
  
  >>> n = Laplace(mu=[[0, 1], [2, 3], [4, 5]], scale=1)
class_docstr_tok: ["Laplace","distribution",".","Parameters","--","--","--","--","--","mean",":","float","or","array","of","float","(","1D","or","2D",")","mean","of","the","distribution","scale",":","float","or","array","of","float","(","1D","or","2D",")",",","must","be","positive","scale","parameter","of","the","distribution",",","same","as","standard","deviation","\/","sqrt","(","2",")","index",":","pd.Index",",","optional",",","default","=","RangeIndex","columns",":","pd.Index",",","optional",",","default","=","RangeIndex","Example","--","--","--","-",">",">",">","from","sktime.proba.laplace","import","Laplace",">",">",">","n","=","Laplace","(","mu=","[","[","0",",","1","]",",","[","2",",","3","]",",","[","4",",","5","]","]",",","scale=1",")"]
docstr: Return expected value of the distribution.
  
  Let :math:`X` be a random variable with the distribution of `self`.
  Returns the expectation :math:`\mathbb{E}[X]`
  
  Returns
  -------
  pd.DataFrame with same rows, columns as `self`
  expected value of distribution (entry-wise)
docstr_tok: ["Return","expected","value","of","the","distribution",".","Let",":","math",":","`","X","`","be","a","random","variable","with","the","distribution","of","`","self","`",".","Returns","the","expectation",":","math",":","`","\\mathbb","{","E","}","[","X","]","`","Returns","--","--","--","-","pd.DataFrame","with","same","rows",",","columns","as","`","self","`","expected","value","of","distribution","(","entry-wise",")"]
code: def mean(self):
      r"""Return expected value of the distribution.
  
      Let :math:`X` be a random variable with the distribution of `self`.
      Returns the expectation :math:`\mathbb{E}[X]`
  
      Returns
      -------
      pd.DataFrame with same rows, columns as `self`
      expected value of distribution (entry-wise)
      """
      mean_arr = self._mu
      return pd.DataFrame(
          mean_arr, index=self.index, columns=self.columns
      )
  
file_path: sktime/sktime/proba/laplace.py
imports: import numpy
  import pandas
  from sktime.proba.base import BaseDistribution
label_desc: Use image node_id 3 for calling the Laplace obj's underlying member method code with example usage: obj.mean() and returns: pd