fit Prophet.py

fitting.py

def fit_predict_model(dataframe, interval_width = 0.99, changepoint_range = 0.8):
    m = Prophet(daily_seasonality = False, yearly_seasonality = False, weekly_seasonality = False,
                seasonality_mode = 'multiplicative', 
                interval_width = interval_width,
                changepoint_range = changepoint_range)
    m = m.fit(dataframe)
    forecast = m.predict(dataframe)
    forecast['fact'] = dataframe['y'].reset_index(drop = True)
    return forecast
    
pred = fit_predict_model(df1)