(self, missing_value_list=None)
Parameters
        ----------
        missing_value_list: list, the value to be replaced. Default None, if is None, it will be set to list of blank, none, null and na,
                            which regarded as missing filled. If not, it can be outlier replace, and missing_value_list includes the outlier values
Parameters
        ----------
        missing_value_list: list, the value to be replaced. Default None, if is None, it will be set to list of blank, none, null and na,
                            which regarded as missing filled. If not, it can be outlier replace, and missing_value_list includes the outlier values
Parameters ---------- missing_value_list : list the value to be replaced . Default None if is None it will be set to list of blank none null and na which regarded as missing filled . If not it can be outlier replace and missing_value_list includes the outlier values
def __init__(self, missing_value_list=None):
        """
        Parameters
        ----------
        missing_value_list: list, the value to be replaced. Default None, if is None, it will be set to list of blank, none, null and na,
                            which regarded as missing filled. If not, it can be outlier replace, and missing_value_list includes the outlier values
        """
        if missing_value_list is None:
            self.missing_value_list = ['', 'none', 'null', 'na', 'None', np.nan]
        else:
            self.missing_value_list = missing_value_list

        self.abnormal_value_list = copy.deepcopy(self.missing_value_list)
        for i, v in enumerate(self.missing_value_list):
            if v != v:
                self.missing_value_list[i] = np.nan
                self.abnormal_value_list[i] = NoneType()

        self.support_replace_method = ['min', 'max', 'mean', 'median', 'designated']
        self.support_output_format = {
            'str': str,
            'float': float,
            'int': int,
            'origin': None
        }

        self.support_replace_area = {
            'min': 'col',
            'max': 'col',
            'mean': 'col',
            'median': 'col',
            'designated': 'col'
        }

        self.cols_fit_impute_rate = []
        self.cols_transform_impute_rate = []
        self.cols_replace_method = []
        self.skip_cols = []
def __init__ ( self , missing_value_list = None ) : if missing_value_list is None : self . missing_value_list = [ '' , 'none' , 'null' , 'na' , 'None' , np . nan ] else : self . missing_value_list = missing_value_list self . abnormal_value_list = copy . deepcopy ( self . missing_value_list ) for i , v in enumerate ( self . missing_value_list ) : if v != v : self . missing_value_list [ i ] = np . nan self . abnormal_value_list [ i ] = NoneType ( ) self . support_replace_method = [ 'min' , 'max' , 'mean' , 'median' , 'designated' ] self . support_output_format = { 'str' : str , 'float' : float , 'int' : int , 'origin' : None } self . support_replace_area = { 'min' : 'col' , 'max' : 'col' , 'mean' : 'col' , 'median' : 'col' , 'designated' : 'col' } self . cols_fit_impute_rate = [ ] self . cols_transform_impute_rate = [ ] self . cols_replace_method = [ ] self . skip_cols = [ ]