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TST : Adding new test case for pivot_table() with Categorical data #21381

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TST : Adding new test case for pivot_table() with Categorical data #21381

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uds5501 Jun 8, 2018
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19 changes: 19 additions & 0 deletions pandas/tests/reshape/test_pivot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -142,6 +142,25 @@ def test_pivot_table_dropna_categoricals(self, dropna):

tm.assert_frame_equal(result, expected)

def test_pivot_with_non_observable_dropna_civ(self, dropna):
# gh-21370
arr = [np.nan, 'low', 'high', 'low', 'high', 'high', np.nan]
df = pd.DataFrame({"In": pd.Categorical(arr,
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Even if this technically passes LINTing I find the indentation very difficult to read. Can you try putting each key of the dict at the start of the line to see if that improves readability?

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alright, I will look into it

categories=['low', 'high'],
ordered=True), "Col": ["A",
"B", "C", "C", "C", "A", "B"],
"Val": range(7)})
result = df.pivot_table(index="In", columns="Col", values="Val",
dropna=dropna)
expected = pd.DataFrame(
{'A': [np.nan, 5], 'B': [1, np.nan], 'C': [3.0, 3.0]},
index=pd.Index(
pd.Categorical.from_codes([0, 1],
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Try moving [0, 1] to the next line and moving the subsequent kwargs up

categories=['low', 'high'],
ordered=True),
name='In'))
tm.assert_frame_equal(result, expected)

def test_pivot_with_non_observable_dropna(self, dropna):
# gh-21133
df = pd.DataFrame(
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