def postprocess(
        self,
        value: pd.DataFrame
        | Styler
        | np.ndarray
        | pl.DataFrame
        | list
        | list[list]
        | dict
        | str
        | None,
    ) -> DataframeData:
        """
        Parameters:
            value: Expects data in any of these formats: `pandas.DataFrame`, `pandas.Styler`, `numpy.array`, `polars.DataFrame`, `list[list]`, `list`, or a `dict` with keys 'data' (and optionally 'headers'), or `str` path to a csv, which is rendered as the spreadsheet.
        Returns:
            the uploaded spreadsheet data as an object with `headers` and `data` keys and optional `metadata` key
        """
        import pandas as pd
        from pandas.io.formats.style import Styler

        if isinstance(value, Styler) and semantic_version.Version(
            pd.__version__
        ) < semantic_version.Version("1.5.0"):
            raise ValueError(
                "Styler objects are only supported in pandas version 1.5.0 or higher. Please try: `pip install --upgrade pandas` to use this feature."
            )
        if isinstance(value, Styler) and self.interactive:
            warnings.warn(
                "Cannot display Styler object in interactive mode. Will display as a regular pandas dataframe instead."
            )

        headers = self.get_headers(value) or self.headers
        data = [] if self.is_empty(value) else self.get_cell_data(value)
        if len(data) == 0:
            return DataframeData(headers=headers, data=[], metadata=None)
        if len(headers) > len(data[0]):
            headers = headers[: len(data[0])]
        elif len(headers) < len(data[0]):
            headers = [
                *headers,
                *[str(i) for i in range(len(headers) + 1, len(data[0]) + 1)],
            ]
        metadata = self.get_metadata(value)
        return DataframeData(
            headers=headers,
            data=data,
            metadata=metadata,  # type: ignore
        )

        Parameters:
            value: Expects data in any of these formats: `pandas.DataFrame`, `pandas.Styler`, `numpy.array`, `polars.DataFrame`, `list[list]`, `list`, or a `dict` with keys 'data' (and optionally 'headers'), or `str` path to a csv, which is rendered as the spreadsheet.
        Returns:
            the uploaded spreadsheet data as an object with `headers` and `data` keys and optional `metadata` key
        
gradio/components/dataframe.py