How to use the modin.pandas.utils.to_pandas function in modin

def boxplot(
        self,
        column=None,
        by=None,
        ax=None,
        fontsize=None,
        rot=0,
        grid=True,
        figsize=None,
        layout=None,
        return_type=None,
        **kwds
    ):
        return to_pandas(self).boxplot(
            column=column,
            by=by,
            ax=ax,
            fontsize=fontsize,
            rot=rot,
            grid=grid,
            figsize=figsize,
            layout=layout,
            return_type=return_type,
            **kwds
        )

right_by=None,
    suffixes=("_x", "_y"),
    tolerance=None,
    allow_exact_matches=True,
    direction="backward",
):
    if not isinstance(left, DataFrame):
        raise ValueError(
            "can not merge DataFrame with instance of type {}".format(type(right))
        )
    ErrorMessage.default_to_pandas("`merge_asof`")
    if isinstance(right, DataFrame):
        right = to_pandas(right)
    return DataFrame(
        pandas.merge_asof(
            to_pandas(left),
            right,
            on=on,
            left_on=left_on,
            right_on=right_on,
            left_index=left_index,
            right_index=right_index,
            by=by,
            left_by=left_by,
            right_by=right_by,
            suffixes=suffixes,
            tolerance=tolerance,
            allow_exact_matches=allow_exact_matches,
            direction=direction,
        )

Modin DataFrame to pandas DataFrame, etc. Currently, pytables
                        does not accept Modin DataFrame objects, so we must convert to
                        pandas.

                    Returns:
                        A Modin DataFrame in place of a pandas DataFrame, or the same
                        return type as pandas.HDFStore.
                    """
                    from .utils import to_pandas

                    # We don't want to constantly be giving this error message for
                    # internal methods.
                    if item[0] != "_":
                        ErrorMessage.default_to_pandas("`{}`".format(item))
                    args = [
                        to_pandas(arg) if isinstance(arg, DataFrame) else arg
                        for arg in args
                    ]
                    kwargs = {
                        k: to_pandas(v) if isinstance(v, DataFrame) else v
                        for k, v in kwargs.items()
                    }
                    obj = super(HDFStore, self).__getattribute__(item)(*args, **kwargs)
                    if isinstance(obj, pandas.DataFrame):
                        return DataFrame(obj)
                    return obj

def lreshape(data, groups, dropna=True, label=None):
    if not isinstance(data, DataFrame):
        raise ValueError("can not lreshape with instance of type {}".format(type(data)))
    ErrorMessage.default_to_pandas("`lreshape`")
    return DataFrame(
        pandas.lreshape(to_pandas(data), groups, dropna=dropna, label=label)
    )

left_by=None,
    right_by=None,
    fill_method=None,
    suffixes=("_x", "_y"),
    how="outer",
):
    if not isinstance(left, DataFrame):
        raise ValueError(
            "can not merge DataFrame with instance of type {}".format(type(right))
        )
    ErrorMessage.default_to_pandas("`merge_ordered`")
    if isinstance(right, DataFrame):
        right = to_pandas(right)
    return DataFrame(
        pandas.merge_ordered(
            to_pandas(left),
            right,
            on=on,
            left_on=left_on,
            right_on=right_on,
            left_by=left_by,
            right_by=right_by,
            fill_method=fill_method,
            suffixes=suffixes,
            how=how,
        )

on=None,
    left_on=None,
    right_on=None,
    left_by=None,
    right_by=None,
    fill_method=None,
    suffixes=("_x", "_y"),
    how="outer",
):
    if not isinstance(left, DataFrame):
        raise ValueError(
            "can not merge DataFrame with instance of type {}".format(type(right))
        )
    ErrorMessage.default_to_pandas("`merge_ordered`")
    if isinstance(right, DataFrame):
        right = to_pandas(right)
    return DataFrame(
        pandas.merge_ordered(
            to_pandas(left),
            right,
            on=on,
            left_on=left_on,
            right_on=right_on,
            left_by=left_by,
            right_by=right_by,
            fill_method=fill_method,
            suffixes=suffixes,
            how=how,
        )

def where(
        self,
        cond,
        other=np.nan,
        inplace=False,
        axis=None,
        level=None,
        errors="raise",
        try_cast=False,
    ):
        if isinstance(other, Series):
            other = to_pandas(other)
        return self._default_to_pandas(
            pandas.Series.where,
            cond,
            other=other,
            inplace=inplace,
            axis=axis,
            level=level,
            errors=errors,
            try_cast=try_cast,
        )

Returns:
                        A Modin DataFrame in place of a pandas DataFrame, or the same
                        return type as pandas.HDFStore.
                    """
                    from .utils import to_pandas

                    # We don't want to constantly be giving this error message for
                    # internal methods.
                    if item[0] != "_":
                        ErrorMessage.default_to_pandas("`{}`".format(item))
                    args = [
                        to_pandas(arg) if isinstance(arg, DataFrame) else arg
                        for arg in args
                    ]
                    kwargs = {
                        k: to_pandas(v) if isinstance(v, DataFrame) else v
                        for k, v in kwargs.items()
                    }
                    obj = super(HDFStore, self).__getattribute__(item)(*args, **kwargs)
                    if isinstance(obj, pandas.DataFrame):
                        return DataFrame(obj)
                    return obj

def wide_to_long(df, stubnames, i, j, sep="", suffix=r"\d+"):
    if not isinstance(df, DataFrame):
        raise ValueError(
            "can not wide_to_long with instance of type {}".format(type(df))
        )
    ErrorMessage.default_to_pandas("`wide_to_long`")
    return DataFrame(
        pandas.wide_to_long(to_pandas(df), stubnames, i, j, sep=sep, suffix=suffix)
    )

right_index=False,
    by=None,
    left_by=None,
    right_by=None,
    suffixes=("_x", "_y"),
    tolerance=None,
    allow_exact_matches=True,
    direction="backward",
):
    if not isinstance(left, DataFrame):
        raise ValueError(
            "can not merge DataFrame with instance of type {}".format(type(right))
        )
    ErrorMessage.default_to_pandas("`merge_asof`")
    if isinstance(right, DataFrame):
        right = to_pandas(right)
    return DataFrame(
        pandas.merge_asof(
            to_pandas(left),
            right,
            on=on,
            left_on=left_on,
            right_on=right_on,
            left_index=left_index,
            right_index=right_index,
            by=by,
            left_by=left_by,
            right_by=right_by,
            suffixes=suffixes,
            tolerance=tolerance,
            allow_exact_matches=allow_exact_matches,
            direction=direction,