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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 as_pandas(self, with_metadata=False):
 """Return this as a pd.DataFrame Parameters with_metadata : bool, default False or dict if True, join data with all meta columns; if a dict, discover meaningful meta columns from values (in key-value) """

        if with_metadata:
            cols = self._discover_meta_cols(**with_metadata) \
                if isinstance(with_metadata, dict) else self.meta.columns
            return (
                self.data
                .set_index(META_IDX)
                .join(self.meta[cols])
                .reset_index()
            )
        else:
            return self.data.copy()