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TST: Added test for pivot_table with int64 dtype and dropna parameter #60374

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merged 3 commits into from
Nov 21, 2024
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TST: Added test for pivot_table with int64 dtype and dropna parameter #60374

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ebdba9c
added tests for int64
AbhishekChaudharii Nov 20, 2024
1f25150
pre-commit changes
AbhishekChaudharii Nov 20, 2024
984b7d6
used pytest.mark.parametrize for expected_dtype
AbhishekChaudharii Nov 21, 2024
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9 changes: 6 additions & 3 deletions pandas/tests/reshape/test_pivot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2376,17 +2376,20 @@ def test_pivot_table_with_margins_and_numeric_columns(self):

tm.assert_frame_equal(result, expected)

def test_pivot_ea_dtype_dropna(self, dropna):
@pytest.mark.parametrize("dtype", ["Int64", "int64"])
def test_pivot_ea_dtype_dropna(self, dropna, dtype):
# GH#47477
df = DataFrame({"x": "a", "y": "b", "age": Series([20, 40], dtype="Int64")})
# GH#47971
df = DataFrame({"x": "a", "y": "b", "age": Series([20, 40], dtype=dtype)})
result = df.pivot_table(
index="x", columns="y", values="age", aggfunc="mean", dropna=dropna
)
expected_dtype = "float64" if dtype == "int64" else "Float64"
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Could you put this in the parametrize instead?

expected = DataFrame(
[[30]],
index=Index(["a"], name="x"),
columns=Index(["b"], name="y"),
dtype="Float64",
dtype=expected_dtype,
)
tm.assert_frame_equal(result, expected)

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