📅  最后修改于: 2022-03-11 14:45:47.332000             🧑  作者: Mango
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)
}