Exécute ce script Python à côté de tes 3 fichiers parquet :

import pandas as pd

preds = pd.read_parquet('predictions_test.parquet').set_index('date')
base  = pd.read_parquet('B_baseline_v14.parquet').set_index('date')
real  = pd.read_parquet('Y_target_v14.parquet').set_index('date')

common = sorted(set(preds.index) & set(base.index) & set(real.index))
rows = []
for d in common:
    row = {'date': str(d)}
    for i in range(96):
        t = f'{i:03d}'
        row[f'l{t}'] = round(float(real.loc[d, f'load_t{t}']), 4)
        row[f'p{t}'] = round(float(preds.loc[d, f'pred_t{t}']), 4)
        row[f'b{t}'] = round(float(base.loc[d, f'baseline_t{t}']), 4)
    rows.append(row)

pd.DataFrame(rows).to_csv('forecast_data.csv', index=False)