Merge z scoring methods

saqc/funcs/outliers.py

@@ -1367,6 +1367,7 @@ class OutliersMixin:
                 )
 
         dat = self._data[field].to_pandas(how="outer")
+
         if min_residuals is None:
             min_residuals = 0
 
@@ -1433,7 +1434,11 @@ class OutliersMixin:
                                 min_periods=min_periods,
                                 method="table",
                             )
-                            .apply(func=np.mean, engine="numba", raw=True)
+                            .apply(
+                                func=np.mean,
+                                raw=True,
+                                engine="numba",
+                            )
                             .iloc[:, 0]
                         )
                         norm = (
@@ -1443,7 +1448,7 @@ class OutliersMixin:
                                 min_periods=min_periods,
                                 method="table",
                             )
-                            .apply(func=np.std, engine="numba", raw=True)
+                            .apply(func=np.std, raw=True, engine="numba")
                             .iloc[:, 0]
                         )
                     else:  # method == 'modified'
@@ -1454,7 +1459,11 @@ class OutliersMixin:
                                 min_periods=min_periods,
                                 method="table",
                             )
-                            .apply(func=np.median, engine="numba", raw=True)
+                            .apply(
+                                func=np.median,
+                                raw=True,
+                                engine="numba",
+                            )
                             .iloc[:, 0]
                         )
                         norm = (
@@ -1466,7 +1475,7 @@ class OutliersMixin:
                                 min_periods=min_periods,
                                 method="table",
                             )
-                            .apply(func=np.median, engine="numba", raw=True)
+                            .apply(func=np.median, raw=True, engine="numba")
                             .iloc[:, 0]
                         )
         residuals = dat.subtract(mod, axis=0).abs()