def METHOD_NAME():
    cloudmask = connection.load_collection("SENTINEL2_L2A_SENTINELHUB",temporal_extent=["2019-02-01", "2019-11-01"],bands=["CLM"])
    l1c = connection.load_collection("SENTINEL2_L1C_SENTINELHUB",
                                     temporal_extent=["2019-02-01", "2019-11-01"],
                                     bands=['B08','B04', 'B8A','B09', 'B11', 'sunAzimuthAngles',
                                            'sunZenithAngles', 'viewAzimuthMean', 'viewZenithMean'])
    start_time = time.time()
    json = l1c.mask(cloudmask).atmospheric_correction().ndvi(nir='B08',red='B04').polygonal_mean_timeseries(polygon).execute()
    elapsed_time = time.time() - start_time
    print("seconds: " + str(elapsed_time))
    from openeo.rest.conversions import timeseries_json_to_pandas
    df = timeseries_json_to_pandas(json)
    l2a = connection.load_collection("SENTINEL2_L2A_SENTINELHUB",
                                     temporal_extent=["2019-02-01", "2019-11-01"], bands=['B08','B04'])
    start_time = time.time()
    l2a_json = l2a.mask(cloudmask).ndvi(nir='B08',red='B04').polygonal_mean_timeseries(polygon).execute()
    elapsed_time = time.time() - start_time
    print("seconds: " + str(elapsed_time))
    df_l2a = timeseries_json_to_pandas(l2a_json)
    import pandas as pd
    df.index = pd.to_datetime(df.index)
    df_l2a.index = pd.to_datetime(df_l2a.index)
    df.name = "iCor"
    df_l2a.name = "Sen2Cor"
    joined = pd.concat([df, df_l2a], axis=1)
    print(joined)
    joined.to_csv('timeseries_icor_masked.csv')