def METHOD_NAME():
    """Create warming stripes for Potsdam
    Source: https://matplotlib.org/matplotblog/posts/warming-stripes/
    """
    request = DwdObservationRequest("temperature_air_200", "annual", "historical").filter_by_name("Hohenpeissenberg")
    values_df = request.values.all().df
    # Definition of years
    first_year = 1781
    last_year = 2020
    first_ref = 1971
    last_ref = 2000
    lim = 0.7  # degrees
    anomaly = values_df.loc[:, "value"]
    reference = anomaly.loc[
        ((values_df.from_date.dt.year >= first_ref) & (values_df.from_date.dt.year <= last_ref))
    ].mean()
    fig, ax = plt.subplots()
    cmap = ListedColormap(
        [
            "#08306b",
            "#08519c",
            "#2171b5",
            "#4292c6",
            "#6baed6",
            "#9ecae1",
            "#c6dbef",
            "#deebf7",
            "#fee0d2",
            "#fcbba1",
            "#fc9272",
            "#fb6a4a",
            "#ef3b2c",
            "#cb181d",
            "#a50f15",
            "#67000d",
        ]
    )
    ax.set_axis_off()
    col = PatchCollection([Rectangle((y, 0), 1, 1) for y in range(first_year, last_year + 1)])
    # set data, colormap and color limits
    col.set_array(anomaly)
    col.set_cmap(cmap)
    col.set_clim(reference - lim, reference + lim)
    ax.add_collection(col)
    ax.set_ylim(0, 1)
    ax.set_xlim(first_year, last_year + 1)
    ax.set_title("Warming stripes for Hohenpeissenberg, Germany\n" "Reference period: 1971 - 2000")
    ax.text(0.05, -0.05, f"{first_year}", ha="center", va="center", transform=ax.transAxes)
    ax.text(0.95, -0.05, f"{last_year}", ha="center", va="center", transform=ax.transAxes)
    ax.text(0.5, -0.05, "Source: Deutscher Wetterdienst", ha="center", va="center", transform=ax.transAxes)
    plt.savefig("hohenpeissenberg_warming_stripes.png")