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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 handle_na(self, data):
 """ Remove rows with NaN values geoms that infer extra information from missing values should override this method. For example :class:`~plotnine.geoms.geom_path`. Parameters data : dataframe Data Returns ------- out : dataframe Data without the NaNs. Notes ----- Shows a warning if the any rows are removed and the `na_rm` parameter is False. It only takes into account the columns of the required aesthetics. """

        return remove_missing(data,
                              self.params['na_rm'],
                              list(self.REQUIRED_AES | self.NON_MISSING_AES),
                              self.__class__.__name__)