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TST: Add a test for multiindex df with na value and adding a new row #53010

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Merged
merged 3 commits into from
May 3, 2023
Merged

TST: Add a test for multiindex df with na value and adding a new row #53010

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7d84878
add test_multiindex_with_na
shteken Apr 30, 2023
dd496f1
Merge branch 'pandas-dev:main' into test-multiindex-with-nan
shteken Apr 30, 2023
7c2a5d1
address comments in pr
shteken May 2, 2023
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16 changes: 16 additions & 0 deletions pandas/tests/test_multilevel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -290,6 +290,22 @@ def test_datetime_object_multiindex(self):

tm.assert_frame_equal(result, expected)

def test_multiindex_with_na(self):
df = DataFrame(
[
["A", np.nan, 1.23, 4.56],
["A", "G", 1.23, 4.56],
["A", "D", 9.87, 10.54],
],
columns=["pivot_0", "pivot_1", "col_1", "col_2"],
)
df.set_index(["pivot_0", "pivot_1"], inplace=True)
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Suggested change
)
df.set_index(["pivot_0", "pivot_1"], inplace=True)
).set_index(["pivot_0", "pivot_1"])

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May I ask what benefit do we gain from chaining the operations?

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We want to avoid inplace=True where possible


df.at[("A", "F"), "col_2"] = 0.0

assert df.loc[("A", "F")]["col_2"] == 0.0
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Instead of these asserts, could you construct expected = DataFrame(...) and then use tm.assert_frame_equal(df, expected)

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Yes. I understand that with your suggestion it would be easier to understand the expected output.

assert pd.isna(df.loc[("A", "F")]["col_1"])


class TestSorted:
"""everything you wanted to test about sorting"""
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