Skip to content
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

Jump to bottom

[TST]: Add test for duplicate keys in concat #36556

Merged
merged 5 commits into from Nov 26, 2020
Merged

[TST]: Add test for duplicate keys in concat #36556

Changes from 1 commit
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
d70e5b2
Add test for 20816
phofl Sep 22, 2020
d5cab80
Modify test
phofl Oct 28, 2020
60399e7
Merge branch 'master' of https://github.com/pandas-dev/pandas into 20816
phofl Oct 28, 2020
7c2e4f9
Move test
phofl Oct 28, 2020
470f289
Merge branch 'master' of https://github.com/pandas-dev/pandas into 20816
phofl Nov 26, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
17 changes: 17 additions & 0 deletions pandas/tests/reshape/test_concat.py
View file
Open in desktop
Expand Up @@ -2927,3 +2927,20 @@ def test_concat_preserves_extension_int64_dtype():
result = pd.concat([df_a, df_b], ignore_index=True)
expected = pd.DataFrame({"a": [-1, None], "b": [None, 1]}, dtype="Int64")
tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize(
("keys", "integrity"),
[
(["red"] * 3, False),
(["red", "blue", "red"], False),
(["red", "blue", "red"], True),
],
)
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Was there a plan to follow the same exact parametrization as in the referenced github issue?
I would suggest to have these tests with verify_integrity=True/False for all keys.

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Was not mentioned as a problem, so I think that was the reason I did not add it. But was more than 4 weeks ago, so I am not quite sure. Added it now.

def test_concat_repeated_keys(keys, integrity):
# GH: 20816
series_list = [pd.Series({"a": 1}), pd.Series({"b": 2}), pd.Series({"c": 3})]
result = pd.concat(series_list, keys=keys, verify_integrity=integrity)
tuples = [(first, second) for first, second in zip(keys, ["a", "b", "c"])]
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I guess this could be simplified.

tuples = list(zip(keys, ["a", "b", "c"]))

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Good point, thank you very much

expected = pd.Series([1, 2, 3], index=pd.MultiIndex.from_tuples(tuples))
tm.assert_series_equal(result, expected)