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alteryx · Sep 28, 2021 · fa4c109 · fa4c109
1 parent b6ad171
commit fa4c109
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Showing 2 changed files with 9 additions and 6 deletions.
diff --git a/evalml/model_understanding/_partial_dependence.py b/evalml/model_understanding/_partial_dependence.py
@@ -142,10 +142,10 @@ def _partial_dependence_calculation(pipeline, grid, features, X):
     else:
         prediction_method = pipeline.predict_proba
 
+    X_eval = X.ww.copy()
     for _, new_values in grid.iterrows():
-        X_eval = X.copy()
         for i, variable in enumerate(features):
-            X_eval.loc[:, variable] = new_values[i]
+            X_eval.ww[variable] = pd.Series([new_values[i]] * X_eval.shape[0])
 
         pred = prediction_method(X_eval)
 

diff --git a/evalml/tests/model_understanding_tests/test_partial_dependence.py b/evalml/tests/model_understanding_tests/test_partial_dependence.py
@@ -1534,15 +1534,18 @@ def test_partial_dependence_categorical_nan(fraud_100):
     )
     pl.fit(X, y)
 
-    dep = partial_dependence(pl, X, features="provider", grid_resolution=5)
+    GRID_RESOLUTION = 5
+    dep = partial_dependence(
+        pl, X, features="provider", grid_resolution=GRID_RESOLUTION
+    )
 
     assert dep.shape[0] == X["provider"].dropna().nunique()
     assert not dep["feature_values"].isna().any()
     assert not dep["partial_dependence"].isna().any()
 
     dep2way = partial_dependence(
-        pl, X, features=("amount", "provider"), grid_resolution=5
+        pl, X, features=("amount", "provider"), grid_resolution=GRID_RESOLUTION
     )
     assert not dep2way.isna().any().any()
-    # Minus 1 in the columns because there is `class_label`
-    assert dep2way.shape == (5, X["provider"].dropna().nunique() + 1)
+    # Plus 1 in the columns because there is `class_label`
+    assert dep2way.shape == (GRID_RESOLUTION, X["provider"].dropna().nunique() + 1)