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TST: Added test that checks if df.sum() results in concatenation instead of dtype coercion to float64 or int64 #63260

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Merged
mroeschke merged 5 commits into from
Dec 6, 2025
+20 −0
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TST: Added test that checks if df.sum() results in concatenation instead of dtype coercion to float64 or int64 #63260

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d2a062b
Added test_sum_string_dtype_coercion that checks summing numeric stri…
AbelJSanchez Dec 4, 2025
ad91b9c
Merge remote-tracking branch 'upstream/main' into sum-string-dtype
AbelJSanchez Dec 5, 2025
8f5b427
Modified test to use pytest.mark.parametrize instead of setting up 3 …
AbelJSanchez Dec 5, 2025
358b2d4
Merge remote-tracking branch 'upstream/main' into sum-string-dtype
AbelJSanchez Dec 6, 2025
719b9e4
Moved Series and Dataframe calls to the body of the test
AbelJSanchez Dec 6, 2025
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19 changes: 19 additions & 0 deletions pandas/tests/frame/test_reductions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1043,6 +1043,25 @@ def test_sum_bools(self):
bools = isna(df)
assert bools.sum(axis=1)[0] == 10

def test_sum_string_dtype_coercion(self):
# GH#22642
# Check that summing numeric strings results in concatenation
# and not conversion to dtype int64 or float64
df = DataFrame({"a": ["483", "3"], "b": ["94", "759"]})
result = df.sum(axis=1)
expected = Series(["48394", "3759"])
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@mroeschke mroeschke Dec 4, 2025

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Could you use pytest.mark.parametrize like

@pytest.mark.parametrize("input_data,expected_data", [[{"a": ...}, ["48394" ...]] ,...])

so we don't have to repeat 3 separate setups?

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@AbelJSanchez AbelJSanchez Dec 4, 2025

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Yes I can. I will make these changes tonight and resubmit.

tm.assert_series_equal(result, expected)

df = DataFrame({"a": ["483.948", "3.0"], "b": ["94.2", "759.93"]})
result = df.sum(axis=1)
expected = Series(["483.94894.2", "3.0759.93"])
tm.assert_series_equal(result, expected)

df = DataFrame({"a": ["483", "3.0"], "b": ["94.2", "79"]})
result = df.sum(axis=1)
expected = Series(["48394.2", "3.079"])
tm.assert_series_equal(result, expected)

# ----------------------------------------------------------------------
# Index of max / min

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