holidays

demo_prophet.py

@@ -2,6 +2,7 @@ import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
 from prophet import Prophet
+import holidays
 import logging
 
 
@@ -9,6 +10,9 @@ import logging
 PREDICTION_LOWER_BOUND = 0 # 15
 print("do not forget about hardwired prediction lower bound", PREDICTION_LOWER_BOUND, "kW")
 
+hungarian_holidays = holidays.Hungary(years=range(2019, 2031))
+HOLIDAY_DF = pd.DataFrame(list(hungarian_holidays.items()), columns=['ds', 'holiday'])
+
 
 def prediction_task(df, split_date, forecast_horizon):
     # Split the data into training (past) and evaluation (future) sets
@@ -18,7 +22,8 @@ def prediction_task(df, split_date, forecast_horizon):
 
     # Initialize and train the Prophet model using the training data
     model = Prophet(seasonality_mode='multiplicative', growth='flat',
-        yearly_seasonality=False, weekly_seasonality=True, daily_seasonality=True)
+        yearly_seasonality=False, weekly_seasonality=True, daily_seasonality=True,
+        holidays=HOLIDAY_DF)
 
     model.fit(train_data)