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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 all(self, **kwargs):
 """Returns whether all the elements are true, potentially over an axis. Return: A new QueryCompiler object containing boolean values or boolean. """

        if self._is_transposed:
            # Pandas ignores on axis=1
            kwargs["bool_only"] = False
            kwargs["axis"] = kwargs.get("axis", 0) ^ 1
            return self.transpose().all(**kwargs)
        return self._process_all_any(lambda df, **kwargs: df.all(**kwargs), **kwargs)