def METHOD_NAME(
    show_fp: bool = False,
    show_sales: bool = False,
    limit: int = 5,
    export: str = "",
    sheet_name: Optional[str] = None,
):
    """Display NFT collections. [Source: https://nftpricefloor.com/]
    Parameters
    ----------
    show_fp : bool
        Show NFT Price Floor for top collections
    limit: int
        Number of NFT collections to display
    export : str
        Export dataframe data to csv,json,xlsx file
    """
    fig = OpenBBFigure()
    df = nftpricefloor_model.get_collections()
    if df.empty:
        return console.print("No data found.", "\n")
    df = df[
        [
            "slug",
            "floorInfo.currentFloorEth",
            "totalSupply",
            "listedCount",
            "blockchain",
        ]
    ]
    if show_fp or show_sales:
        fig = OpenBBFigure(yaxis_title="Floor Price [ETH]" if show_fp else "Sales")
        fig.set_title("Collections Floor Price" if show_fp else "Collections Sales")
        for collection in df["slug"].head(limit).values:
            df_collection = nftpricefloor_model.get_floor_price(collection)
            df_collection.index = pd.DatetimeIndex(
                df_collection.index.rename("date").strftime("%Y-%m-%d")
            )
            if not df_collection.empty:
                values = (
                    df_collection["floorEth"].values
                    if show_fp
                    else df_collection["salesCount"].values
                )
                fig.add_scatter(
                    x=df_collection.index, y=values, mode="lines", name=collection
                )
        if not fig.is_image_export(export):
            fig.show()
    print_rich_table(
        df,
        headers=list(df.columns),
        show_index=False,
        title="NFT Collections",
        export=bool(export),
        limit=limit,
    )
    return export_data(
        export,
        os.path.dirname(os.path.abspath(__file__)),
        "collections",
        df,
        sheet_name,
        fig,
    )