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- wind_data = pd.read_csv("data/ninja_wind_europe_v1.1_current_on-offshore.csv")
- solar_data = pd.read_csv("data/ninja_pv_europe_v1.1_merra2.csv")
- wind_data['time'] = pd.to_datetime(wind_data['time'], format="%Y-%m-%d %H:%M:%S")
- solar_data['time'] = pd.to_datetime(solar_data['time'], format="%Y-%m-%d %H:%M:%S")
- regions_labels = sorted(list(solar_data.columns))
- regions_labels.remove("time")
- offshore_labels = {x for x in wind_data.columns if '_OFF' in x}
- missing_offshore = {f"{x}_OFF" for x in regions_labels} - offshore_labels
- for x in missing_offshore:
- wind_data[x] = 0
- offshore_labels = [x for x in wind_data.columns if '_OFF' in x]
- onshore_labels = [x for x in wind_data.columns if '_ON' in x]
- offshore = wind_data[["time"] + offshore_labels]
- onshore = wind_data[["time"] + onshore_labels]
- solar = solar_data.set_index("time").stack().rename("solar")
- print(solar.index.names)
- solar.index.names = ["time", "region"]
- offshore.set_index("time", inplace=True)
- offshore.columns = map(lambda x: x.replace("_OFF", ""), offshore.columns)
- offshore = offshore.stack().rename("offshore")
- offshore.index.names = ["time", "region"]
- onshore.set_index("time", inplace=True)
- onshore.columns = map(lambda x: x.replace("_ON", ""), onshore.columns)
- onshore = onshore.stack().rename("onshore")
- onshore.index.names = ["time", "region"]
- potential = pd.DataFrame(offshore)
- print(potential)
- potential = potential.merge(pd.DataFrame(onshore), left_index=True, right_index=True, how="outer")
- print(potential)
- potential = potential.merge(pd.DataFrame(solar), left_index=True, right_index=True, how="outer")
- print(potential)
- potential.sort_values(["time", "region"], inplace=True)
- potential.to_parquet("data/potential.parquet")
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