Pusn test up and add observed fixture

Author: ryankarlos

pandas/tests/reshape/test_pivot.py

@@ -1656,6 +1656,41 @@ def test_categorical_margins_category(self, observed):
  table = df.pivot_table("x", "y", "z", dropna=observed, margins=True)
  tm.assert_frame_equal(table, expected)
 
+ def test_pivot_with_categorical(self, observed):
+ # gh-21370
+ idx = [np.nan, "low", "high", "low", np.nan]
+ col = [np.nan, "A", "B", np.nan, "A"]
+ df = pd.DataFrame(
+ {
+ "In": pd.Categorical(idx, categories=["low", "high"], ordered=True),
+ "Col": pd.Categorical(col, categories=["A", "B"], ordered=True),
+ "Val": range(1, 6),
+ }
+ )
+ # case with index/columns/value
+ result = df.pivot_table(index="In", columns="Col", values="Val")
+
+ expected_cols = pd.CategoricalIndex(["A", "B"], ordered=True, name="Col")
+
+ expected = pd.DataFrame(
+ data=[[2.0, np.nan], [np.nan, 3.0]], columns=expected_cols
+ )
+ expected.index = Index(
+ pd.Categorical(["low", "high"], categories=["low", "high"], ordered=True),
+ name="In",
+ )
+
+ tm.assert_frame_equal(result, expected)
+
+ # case with columns/value
+ result = df.pivot_table(columns="Col", values="Val")
+
+ expected = pd.DataFrame(
+ data=[[3.5, 3.0]], columns=expected_cols, index=Index(["Val"])
+ )
+
+ tm.assert_frame_equal(result, expected)
+
  def test_categorical_aggfunc(self, observed):
  # GH 9534
  df = pd.DataFrame(
@@ -2554,38 +2589,3 @@ def test_margin_normalize(self):
  names=["A", "B"],
  )
  tm.assert_frame_equal(result, expected)
-
- def test_pivot_with_categorical(self):
- # gh-21370
- idx = [np.nan, "low", "high", "low", np.nan]
- col = [np.nan, "A", "B", np.nan, "A"]
- df = pd.DataFrame(
- {
- "In": pd.Categorical(idx, categories=["low", "high"], ordered=True),
- "Col": pd.Categorical(col, categories=["A", "B"], ordered=True),
- "Val": range(1, 6),
- }
- )
- # case with index/columns/value
- result = df.pivot_table(index="In", columns="Col", values="Val")
-
- expected_cols = pd.CategoricalIndex(["A", "B"], ordered=True, name="Col")
-
- expected = pd.DataFrame(
- data=[[2.0, np.nan], [np.nan, 3.0]], columns=expected_cols
- )
- expected.index = Index(
- pd.Categorical(["low", "high"], categories=["low", "high"], ordered=True),
- name="In",
- )
-
- tm.assert_frame_equal(result, expected)
-
- # case with columns/value
- result = df.pivot_table(columns="Col", values="Val")
-
- expected = pd.DataFrame(
- data=[[3.5, 3.0]], columns=expected_cols, index=Index(["Val"])
- )
-
- tm.assert_frame_equal(result, expected)