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TST: Inconsistent behavior of .replace() in Int64 series with NA #38693

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Merged
merged 13 commits into from
Dec 28, 2020
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TST: Inconsistent behavior of .replace() in Int64 series with NA #38693

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39ec797
pandas-dev issue #38267
ftrihardjo Dec 25, 2020
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pandas-dev issue #38267
ftrihardjo Dec 25, 2020
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pandas-dev issue #38267
ftrihardjo Dec 26, 2020
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pandas-dev issue #38267
ftrihardjo Dec 26, 2020
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pandas-dev issue #38267
ftrihardjo Dec 26, 2020
9d437ec
pandas-dev issue #38267
ftrihardjo Dec 26, 2020
76e2fa6
pandas-dev issue #38267
ftrihardjo Dec 27, 2020
6320412
pandas-dev issue #38267
ftrihardjo Dec 27, 2020
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pandas-dev issue #38267
ftrihardjo Dec 27, 2020
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pandas-dev issue #38267
ftrihardjo Dec 27, 2020
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pandas-dev issue #38267
ftrihardjo Dec 27, 2020
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pandas-dev issue #38267
ftrihardjo Dec 28, 2020
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pandas-dev issue #38267
ftrihardjo Dec 28, 2020
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7 changes: 7 additions & 0 deletions pandas/tests/series/methods/test_replace.py
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Original file line number Diff line number Diff line change
Expand Up @@ -208,6 +208,13 @@ def test_replace_with_dict_with_bool_keys(self):
expected = pd.Series(["yes", False, "yes"])
tm.assert_series_equal(result, expected)

@pytest.mark.parametrize("dtype", ["int8", "int16", "int32", "int64"])
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@MarcoGorelli MarcoGorelli Dec 26, 2020

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the types need to be capitalised, as in the issue, e.g. Int64 not int64

def test_replace_int_with_na(self, dtype):
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@arw2019 arw2019 Dec 27, 2020

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should use any_nullable_int_dtype fixture here

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@arw2019 arw2019 Dec 27, 2020

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I'd call it test_replace_nullable_int_with_na or test_replace_Int_with_na

# GH 38267
result = pd.Series([0, None]).astype(dtype).replace(0, pd.NA)
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@arw2019 arw2019 Dec 27, 2020

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pass dtype directly to the Series constructor

expected = pd.Series([pd.NA, pd.NA])
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@arw2019 arw2019 Dec 27, 2020

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you also need to pass dtype here else (looking at CI output) this casts to object. That's why currently this test doesn't actually pass

tm.assert_series_equal(result, expected)

def test_replace2(self):
N = 100
ser = pd.Series(np.fabs(np.random.randn(N)), tm.makeDateIndex(N), dtype=object)
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