Exemplo n.º 1
0
def create_temperature_ts_plot():
    """ Create plot for README sketch """
    stations = DwdObservationRequest(
        DwdObservationParameterSet.CLIMATE_SUMMARY,
        DwdObservationResolution.DAILY, DwdObservationPeriod.HISTORICAL)

    df = stations.all()

    station_id, _, _, height, lat, lon, name, state = df.sort_values(
        "FROM_DATE").iloc[0].values
    name = name.replace(u"ß", "ss")

    data = DwdObservationValues(
        [station_id],
        DwdObservationParameter.DAILY.TEMPERATURE_AIR_200,
        DwdObservationResolution.DAILY,
        period=[DwdObservationPeriod.HISTORICAL])

    df = data.all()

    df_annual = df.groupby(df.DATE.dt.year)["VALUE"].mean().reset_index()
    df_annual["DATE"] = pd.to_datetime(df_annual["DATE"], format="%Y")

    temp_mean = df["VALUE"].mean()

    fig, ax = plt.subplots(tight_layout=True)

    df.plot("DATE",
            "VALUE",
            ax=ax,
            color="blue",
            label="Tmean,daily",
            legend=False)
    df_annual.plot("DATE",
                   "VALUE",
                   ax=ax,
                   color="orange",
                   label="Tmean,annual",
                   legend=False)
    ax.axhline(y=temp_mean, color="red", label="mean(Tmean,daily)")

    ax.text(0.2,
            0.05,
            "Source: Deutscher Wetterdienst",
            ha='center',
            va='center',
            transform=ax.transAxes)

    ax.set_xlabel("Date")

    title = f"temperature (°C) at {name} (GER)\n" \
            f"ID {station_id}\n" \
            f"{lat}N {lon}E {height}m"
    ax.set_title(title)
    ax.legend(facecolor="white")

    ax.margins(x=0)

    plt.savefig(f"temperature_ts.png")
Exemplo n.º 2
0
def create_weather_stations_map():
    """ Create map of DWD weather stations_result in Germany """
    stations = DwdObservationRequest(DwdObservationDataset.CLIMATE_SUMMARY,
                                     DwdObservationResolution.DAILY,
                                     DwdObservationPeriod.HISTORICAL)

    stations_df = stations.all().df

    fig, ax = plt.subplots()

    # Rainbow colormap
    cmap = colors.LinearSegmentedColormap.from_list("", [
        '#86007D',
        '#0000F9',
        '#008018',
        '#FFFF41',
        '#FFA52C',
        '#FF0018',
    ])

    bounds = stations_df.height.quantile(
        [0, 0.16666667, 0.33333333, 0.5, 0.66666667, 0.83333333, 1]).values

    norm = colors.BoundaryNorm(bounds, cmap.N)

    stations_df = stations_df.rename(columns={"height": "Height [m]"})

    stations_df.plot.scatter(x="longitude",
                             y="latitude",
                             c="Height [m]",
                             cmap=cmap,
                             norm=norm,
                             ax=ax)

    ax.set_xlabel("Longitude [°]")
    ax.set_ylabel("Latitude [°]")
    ax.set_title("German weather stations_result")

    ax.text(0.3,
            0.05,
            "Source: Deutscher Wetterdienst",
            ha='center',
            va='center',
            transform=ax.transAxes)

    plt.savefig("german_weather_stations.png")

    return