Skip to content

TST: Check map function works with StringDtype (#40823) #41723

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 6 commits into from
Jun 2, 2021
Merged

TST: Check map function works with StringDtype (#40823) #41723

Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
b59d6b8
TST: Check map function works with StringDType (#40823).
mdhsieh May 29, 2021
590396d
TST: Remove unused imports.
mdhsieh May 29, 2021
c707f1b
TST: Remove new test file since want to add test in existing file.
mdhsieh Jun 1, 2021
d8347c8
TST: Add new test to pandas/tests/apply/test_series_apply.py
mdhsieh Jun 1, 2021
bf85840
TST: Add updated test on Series (#40823).
mdhsieh Jun 1, 2021
078b1b6
TST: Change StringDType to any string data type.
mdhsieh Jun 1, 2021
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
14 changes: 14 additions & 0 deletions pandas/tests/apply/test_series_apply.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -115,6 +115,20 @@ def func(x):
ser.apply(func)


def test_series_map_stringdtype(any_string_dtype):
# map test on StringDType, GH#40823
ser1 = Series(
data=["cat", "dog", "rabbit"],
index=["id1", "id2", "id3"],
dtype=any_string_dtype,
)
ser2 = Series(data=["id3", "id2", "id1", "id7000"], dtype=any_string_dtype)
result = ser2.map(ser1)
expected = Series(data=["rabbit", "dog", "cat", pd.NA], dtype=any_string_dtype)

tm.assert_series_equal(result, expected)


def test_apply_box():
# ufunc will not be boxed. Same test cases as the test_map_box
vals = [pd.Timestamp("2011-01-01"), pd.Timestamp("2011-01-02")]
Expand Down