def pre_process_dataset(dataset_path):
            """Restrict the time axis and add the weather data"""
            df = pd.read_csv(dataset_path, index_col=0)
            # convert time index
            df.index = pd.DatetimeIndex(pd.to_datetime(df.index, utc=True)).tz_localize(
                None
            )
            # extract pre-determined period
            df = df.loc[
                (pd.Timestamp("2015-01-01") <= df.index)
                & (df.index <= pd.Timestamp("2022-08-31"))
            ]
            # download and preprocess the weather information
            df_weather = self._download_weather_data()
            # add weather data as additional features
            df = pd.concat([df, df_weather], axis=1)
            # interpolate weather data
            df = df.interpolate()
            # raining duration is given in minutes -> we divide by 4 from hourly to quarter-hourly records
            df["RainDur [min]"] = df["RainDur [min]"] / 4

            # round Electricity cols to 4 decimals, other columns to 2 decimals
            cols_precise = ["Value_NE5", "Value_NE7"]
            df = df.round(
                decimals={col: (4 if col in cols_precise else 2) for col in df.columns}
            )

            # export the dataset
            df.index.name = "Timestamp"
            df.to_csv(self._get_path_dataset())
Restrict the time axis and add the weather data
darts/datasets/__init__.py