def METHOD_NAME():
    pivot_df = pp.pivot(
        df=single_metric_df,
        index=["dttm"],
        columns=["country"],
        aggregates={"sum_metric": {"operator": "sum"}},
    )
    """
                   sum_metric
    country            UK US
    dttm
    2019-01-01          5  6
    2019-01-02          7  8
    """
    rolling_df = pp.rolling(
        df=pivot_df,
        columns={"sum_metric": "sum_metric"},
        rolling_type="sum",
        window=2,
        min_periods=0,
    )
    """
               sum_metric
    country            UK    US
    dttm
    2019-01-01          5     6
    2019-01-02         12    14
    """
    flat_df = pp.flatten(rolling_df)
    """
            dttm  sum_metric, UK  sum_metric, US
    0 2019-01-01               5               6
    1 2019-01-02              12              14
    """
    assert flat_df.equals(
        pd.DataFrame(
            data={
                "dttm": pd.to_datetime(["2019-01-01", "2019-01-02"]),
                FLAT_COLUMN_SEPARATOR.join(["sum_metric", "UK"]): [5, 12],
                FLAT_COLUMN_SEPARATOR.join(["sum_metric", "US"]): [6, 14],
            }
        )
    )