def METHOD_NAME(state):
    state_obj = us.states.lookup(state)
    fips = int(state_obj.fips)
    # Get the right rows
    rows = ForecastData.data[(ForecastData.data["fips"] == fips)]
    rows = rows.drop(columns="fips")
    rows["date"] = pd.to_datetime(rows["date"])
    rows = rows.set_index("date")
    rows.columns = ["nC", "nD"]
    # Format the data as tuples
    nC_forecast = [
        ((index - ForecastData.ref_date).days, value / 7.0)
        for (index, value) in rows.nC.items()
    ]
    nD_forecast = [
        ((index - ForecastData.ref_date).days, value / 7.0)
        for (index, value) in rows.nD.items()
    ]
    return (nC_forecast, nD_forecast)