augmented_dickey_fuller.py

def augmented_dickey_fuller_statistics(time_series):
    """
    Run the augmented Dickey-Fuller test on a time series
    to determine if it's stationary.
    Arguments: 
        time_series: series. Time series that we want to test 
    Outputs: 
        Test statistics for the Augmented Dickey Fuller test in 
        the console 
    """
    result = adfuller(time_series.values)
    print('ADF Statistic: %f' % result[0])
    print('p-value: %f' % result[1])
    print('Critical Values:')
    for key, value in result[4].items():
        print('\t%s: %.3f' % (key, value)) 

#Execute in the main block

#Run each transformed, differenced time series thru the Augmented Dickey Fuller test
print('Augmented Dickey-Fuller Test: Electricity Price Time Series')
  augmented_dickey_fuller_statistics(master_df['Electricity_Price_Transformed_Differenced'].dropna())
print('Augmented Dickey-Fuller Test: Natural Gas Price Time Series')
    augmented_dickey_fuller_statistics(master_df['Nat_Gas_Price_MCF_Transformed_Differenced'].dropna())