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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def convert_to_ten_digit_int(self, column: pd.Series) -> pd.Series: """Converts a column of datetimes, integers, or floats into a column of 10 digit integers. Parameters column : A series of datetimes, integers, or floats. Returns ------- pd.Series A series of ten digit integers based on the input data. Raises ------ RandomnessError : If the column contains data that is neither a datetime-like nor numeric. """

        if isinstance(column.iloc[0], datetime.datetime):
            column = self.clip_to_seconds(column.astype(int))
        elif np.issubdtype(column.iloc[0], np.integer):
            if not len(column >= 0) == len(column):
                raise RandomnessError("Values in integer columns must be greater than or equal to zero.")
            column = self.spread(column)
        elif np.issubdtype(column.iloc[0], np.floating):
            column = self.shift(column)
        else:
            raise RandomnessError(f"Unhashable column type {type(column.iloc[0])}. "
                                  "IndexMap accepts datetime like columns and numeric columns.")
        return column