modified: pandas/tests/reshape/test_pivot_multilevel.py

	- Combined tests :func:`test_pivot_table_values_in_columns` and :func:`test_pivot_table_values_in_index` into a single parametrized test, :func:`test_pivot_table_multiindex_values_as_two_params` to reduce duplicate setup code.

Author: it176131

pandas/tests/reshape/test_pivot_multilevel.py

@@ -252,47 +252,43 @@ def test_pivot_df_multiindex_index_none():
     tm.assert_frame_equal(result, expected)
 
 
-def test_pivot_table_values_in_columns():
+@pytest.mark.parametrize(
+    argnames=["index", "columns"],
+    argvalues=[("index", ["col", "value"]), (["index", "value"], "col")],
+    ids=["values-and-columns", "values-and-index"],
+)
+def test_pivot_table_multiindex_values_as_two_params(index, columns, request):
     data = [
         ["A", 1, 50, -1],
         ["B", 1, 100, -2],
         ["A", 2, 100, -2],
         ["B", 2, 200, -4],
     ]
     df = pd.DataFrame(data=data, columns=["index", "col", "value", "extra"])
-    result = df.pivot_table(values="value", index="index", columns=["col", "value"])
+    result = df.pivot_table(values="value", index=index, columns=columns)
     nan = np.nan
-    e_data = [
-        [50.0, nan, 100.0, nan],
-        [nan, 100.0, nan, 200.0],
-    ]
-    e_index = Index(data=["A", "B"], name="index")
-    e_cols = MultiIndex.from_arrays(
-        arrays=[[1, 1, 2, 2], [50, 100, 100, 200]], names=["col", "value"]
-    )
-    expected = pd.DataFrame(data=e_data, index=e_index, columns=e_cols)
-    tm.assert_frame_equal(left=result, right=expected)
+    if request.node.callspec.id == "values-and-columns":
+        e_data = [
+            [50.0, nan, 100.0, nan],
+            [nan, 100.0, nan, 200.0],
+        ]
+        e_index = Index(data=["A", "B"], name="index")
+        e_cols = MultiIndex.from_arrays(
+            arrays=[[1, 1, 2, 2], [50, 100, 100, 200]], names=["col", "value"]
+        )
+        expected = pd.DataFrame(data=e_data, index=e_index, columns=e_cols)
 
+    else:
+        e_data = [
+            [50.0, nan],
+            [nan, 100.0],
+            [100.0, nan],
+            [nan, 200.0],
+        ]
+        e_index = MultiIndex.from_arrays(
+            arrays=[["A", "A", "B", "B"], [50, 100, 100, 200]], names=["index", "value"]
+        )
+        e_cols = Index(data=[1, 2], name="col")
+        expected = pd.DataFrame(data=e_data, index=e_index, columns=e_cols)
 
-def test_pivot_table_values_in_index():
-    data = [
-        ["A", 1, 50, -1],
-        ["B", 1, 100, -2],
-        ["A", 2, 100, -2],
-        ["B", 2, 200, -4],
-    ]
-    df = pd.DataFrame(data=data, columns=["index", "col", "value", "extra"])
-    result = df.pivot_table(values="value", index=["index", "value"], columns="col")
-    nan = np.nan
-    e_data = [
-        [50.0, nan],
-        [nan, 100.0],
-        [100.0, nan],
-        [nan, 200.0],
-    ]
-    e_index = MultiIndex.from_arrays(
-        arrays=[["A", "A", "B", "B"], [50, 100, 100, 200]], names=["index", "value"]
-    )
-    e_cols = Index(data=[1, 2], name="col")
-    expected = pd.DataFrame(data=e_data, index=e_index, columns=e_cols)
     tm.assert_frame_equal(left=result, right=expected)