def _download_weather_data():
        """Concatenate the yearly csv files into a single dataframe and reshape it"""
        # download the csv from the url
        base_url = "https://data.stadt-zuerich.ch/dataset/ugz_meteodaten_stundenmittelwerte/download/"
        filenames = [f"ugz_ogd_meteo_h1_{year}.csv" for year in range(2015, 2023)]
        df = pd.concat([pd.read_csv(base_url + fname) for fname in filenames])
        # retain only one weather station
        df = df.loc[df["Standort"] == "Zch_Stampfenbachstrasse"]
        # pivot the df to get all measurements as columns
        df["param_name"] = df["Parameter"] + " [" + df["Einheit"] + "]"
        df = df.pivot(index="Datum", columns="param_name", values="Wert")
        # convert time index to from CET to UTC and extract the required time range
        df.index = pd.DatetimeIndex(pd.to_datetime(df.index, utc=True)).tz_localize(
            None
        )
        df = df.loc[
            (pd.Timestamp("2015-01-01") <= df.index)
            & (df.index <= pd.Timestamp("2022-08-31"))
        ]
        return df
Concatenate the yearly csv files into a single dataframe and reshape it
darts/datasets/__init__.py