parameters: (self, X)
return_statement: return X
docstring: Center and scale the data.
  
          Parameters
          ----------
          X : {array-like, sparse matrix}
              The data used to scale along the specified axis.
docstring_summary: Center and scale the data.
docstring_tokens: Center and scale the data .
function: def transform(self, X):
          """Center and scale the data.
  
          Parameters
          ----------
          X : {array-like, sparse matrix}
              The data used to scale along the specified axis.
          """
          check_is_fitted(self)
          X = check_array(X, accept_sparse=('csr', 'csc'), copy=self.copy,
                          estimator=self, dtype=FLOAT_DTYPES,
                          force_all_finite='allow-nan')
  
          if sparse.issparse(X):
              if self.with_scaling:
                  inplace_column_scale(X, 1.0 / self.scale_)
          else:
              if self.with_centering:
                  X -= self.center_
              if self.with_scaling:
                  X /= self.scale_
          return X
function_tokens: def transform ( self , X ) : check_is_fitted ( self ) X = check_array ( X , accept_sparse = ( 'csr' , 'csc' ) , copy = self . copy , estimator = self , dtype = FLOAT_DTYPES , force_all_finite = 'allow-nan' ) if sparse . issparse ( X ) : if self . with_scaling : inplace_column_scale ( X , 1.0 / self . scale_ ) else : if self . with_centering : X -= self . center_ if self . with_scaling : X /= self . scale_ return X