Skip to content

TST: a weird bug with numpy + DataFrame with duplicate columns #38354

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 8 commits into from
Dec 8, 2020
Merged

TST: a weird bug with numpy + DataFrame with duplicate columns #38354

Changes from all commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
83cfd98
Add test_masking_duplicate_columns
GabrielSimonetto Oct 14, 2020
16e47c3
Update test to use mixed dtypes
GabrielSimonetto Oct 16, 2020
e6ab566
Requested Changes
GabrielSimonetto Oct 16, 2020
fc746a4
Add np constructor to test
GabrielSimonetto Oct 18, 2020
b62fe2e
Black changes
GabrielSimonetto Oct 18, 2020
51b2095
Merge branch 'master' of https://github.com/pandas-dev/pandas into GH…
arw2019 Dec 8, 2020
d637b1b
review comments: exact OP
arw2019 Dec 8, 2020
4819df4
parametrize test
arw2019 Dec 8, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
33 changes: 33 additions & 0 deletions pandas/tests/frame/test_nonunique_indexes.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -486,3 +486,36 @@ def test_set_value_by_index(self):

df.iloc[:, 0] = 3
tm.assert_series_equal(df.iloc[:, 1], expected)

@pytest.mark.parametrize(
"data1,data2,expected_data",
(
(
[[1, 2], [3, 4]],
[[0.5, 6], [7, 8]],
[[np.nan, 3.0], [np.nan, 4.0], [np.nan, 7.0], [6.0, 8.0]],
),
(
[[1, 2], [3, 4]],
[[5, 6], [7, 8]],
[[np.nan, 3.0], [np.nan, 4.0], [5, 7], [6, 8]],
),
),
)
def test_masking_duplicate_columns_mixed_dtypes(
self,
data1,
data2,
expected_data,
):
# GH31954

df1 = DataFrame(np.array(data1))
df2 = DataFrame(np.array(data2))
df = pd.concat([df1, df2], axis=1)

result = df[df > 2]
expected = DataFrame(
{i: np.array(col) for i, col in enumerate(expected_data)}
).rename(columns={2: 0, 3: 1})
tm.assert_frame_equal(result, expected)