feat: add adfuller stationary test parameters to config

alexbarros · fabclmnt · commit 3642b01fedd2 · 2024-10-28T17:41:36.000Z
diff --git a/src/ydata_profiling/config.py b/src/ydata_profiling/config.py
@@ -1,7 +1,7 @@
 """Configuration for the package."""
 from enum import Enum
 from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, Dict, List, Literal, Optional, Tuple, Union
 
 import yaml
 from pydantic.v1 import BaseModel, BaseSettings, Field, PrivateAttr
@@ -112,6 +112,8 @@ class TimeseriesVars(BaseModel):
     lags: List[int] = [1, 7, 12, 24, 30]
     significance: float = 0.05
     pacf_acf_lag: int = 100
+    autolag: Optional[Literal["AIC", "BIC", "t-stat"]] = "AIC"
+    maxlag: Optional[int] = None
 
 
 class Univariate(BaseModel):
diff --git a/src/ydata_profiling/model/pandas/describe_timeseries_pandas.py b/src/ydata_profiling/model/pandas/describe_timeseries_pandas.py
@@ -16,12 +16,15 @@
 
 
 def stationarity_test(config: Settings, series: pd.Series) -> Tuple[bool, float]:
-    significance_threshold = config.vars.timeseries.significance
-
     # make sure the data has no missing values
-    adfuller_test = adfuller(series.dropna())
+    adfuller_test = adfuller(
+        series.dropna(),
+        autolag=config.vars.timeseries.autolag,
+        maxlag=config.vars.timeseries.maxlag
+    )
     p_value = adfuller_test[1]
 
+    significance_threshold = config.vars.timeseries.significance
     return p_value < significance_threshold, p_value
 
 
