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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 reindex(self, axis, labels, **kwargs):
 """Fits a new index for this Manger. Args: axis: The axis index object to target the reindex on. labels: New labels to conform 'axis' on to. Returns: A new QueryCompiler with updated data and new index. """


        # To reindex, we need a function that will be shipped to each of the
        # partitions.
        def reindex_builer(df, axis, old_labels, new_labels, **kwargs):
            if axis:
                while len(df.columns) < len(old_labels):
                    df[len(df.columns)] = np.nan
                df.columns = old_labels
                new_df = df.reindex(columns=new_labels, **kwargs)
                # reset the internal columns back to a RangeIndex
                new_df.columns = pandas.RangeIndex(len(new_df.columns))
                return new_df
            else:
                while len(df.index) < len(old_labels):
                    df.loc[len(df.index)] = np.nan
                df.index = old_labels
                new_df = df.reindex(index=new_labels, **kwargs)
                # reset the internal index back to a RangeIndex
                new_df.reset_index(inplace=True, drop=True)
                return new_df

        old_labels = self.columns if axis else self.index
        new_index = self.index if axis else labels
        new_columns = labels if axis else self.columns
        func = self._prepare_method(
            lambda df: reindex_builer(df, axis, old_labels, labels, **kwargs)
        )
        # The reindex can just be mapped over the axis we are modifying. This
        # is for simplicity in implementation. We specify num_splits here
        # because if we are repartitioning we should (in the future).
        # Additionally this operation is often followed by an operation that
        # assumes identical partitioning. Internally, we *may* change the
        # partitioning during a map across a full axis.
        new_data = self._map_across_full_axis(axis, func)
        return self.__constructor__(new_data, new_index, new_columns)