obtain_adf_kpss_results.py

def obtain_adf_kpss_results(timeseries, max_d):
    """ Build dataframe with ADF statistics and p-value for time series after applying difference on time series
    
    Args:
        time_series (df): Dataframe of univariate time series  
        max_d (int): Max value of how many times apply difference
        
    Returns:
        Dataframe showing values of ADF statistics and p when applying ADF test after applying d times 
        differencing on a time-series.
    
    """
    
    results=[]

    for idx in range(max_d):
        adf_result = adfuller(timeseries, autolag='AIC')
        kpss_result = kpss(timeseries, regression='c', nlags="auto")
        timeseries = timeseries.diff().dropna()
        if adf_result[1] <=0.05:
            adf_stationary = True
        else:
            adf_stationary = False
        if kpss_result[1] <=0.05:
            kpss_stationary = False
        else:
            kpss_stationary = True
            
        stationary = adf_stationary & kpss_stationary
            
        results.append((idx,adf_result[1], kpss_result[1],adf_stationary,kpss_stationary, stationary))
    
    # Construct DataFrame 
    results_df = pd.DataFrame(results, columns=['d','adf_stats','p-value', 'is_adf_stationary','is_kpss_stationary','is_stationary' ])
    
    return results_df