Automatic stationary conversion

def make_stationary(data: pd.Series, alpha: float = 0.05, max_diff_order: int = 10) -> dict:
    # Test to see if the time series is already stationary
    if adfuller(data)[1] < alpha:
        return {
            'differencing_order': 0,
            'time_series': np.array(data)
        }
    
    # A list to store P-Values
    p_values = []
    
    # Test for differencing orders from 1 to max_diff_order (included)
    for i in range(1, max_diff_order + 1):
        # Perform ADF test
        result = adfuller(data.diff(i).dropna())
        # Append P-value
        p_values.append((i, result[1]))
        
    # Keep only those where P-value is lower than significance level
    significant = [p for p in p_values if p[1] < alpha]
    # Sort by the differencing order
    significant = sorted(significant, key=lambda x: x[0])
    
    # Get the differencing order
    diff_order = significant[0][0]
    
    # Make the time series stationary
    stationary_series = data.diff(diff_order).dropna()
    
    return {
        'differencing_order': diff_order,
        'time_series': np.array(stationary_series)
    }

Source: gist.githubusercontent.com

Similar codes

2 votes188 views1 answer
Add numpy array to pandas dataframe
Python
0 vote180 views1 answer
Make value of two tables unique django
Python
0 vote194 views1 answer
Merge two list of dictionaries python with string
Python
3 votes178 views3 answers
How to remove items from list in python
Python
45 votes170 views3 answers
Convert integer to string python
Python
10 votes171 views9 answers
Google traduction
Python
1 vote172 views2 answers
Python tkinter button click show label event
Python
21 votes166 views5 answers
Basic tkinter window
Python
0 vote175 views1 answer
Pyspark rdd method
Python
0 vote172 views1 answer
Ad background image with tkinter
Python