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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 drop_nan(self, col: str=None, method: str="all", **kwargs):
 """ Drop rows with NaN values from the main dataframe :param col: name of the column, defaults to None. Drops in all columns if no value is provided :type col: str, optional :param method: ``how`` param for ``df.dropna``, defaults to "all" :type method: str, optional :param \*\*kwargs: params for ``df.dropna`` :type \*\*kwargs: optional :example: ``ds.drop_nan("mycol")`` """

        try:
            if col is None:
                self.df = self.df.dropna(how=method, **kwargs)
            else:
                self.df = self.df[self.df[col].notnull()]
        except Exception as e:
            self.err(e, "Error dropping nan values")