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BUG: Don't cast categorical nan to int #28438

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Merged
merged 18 commits into from
Sep 18, 2019
Merged

BUG: Don't cast categorical nan to int #28438

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9dd2dbe
Don't cast categorical nan to int
Sep 12, 2019
952114f
Parametrize test
Sep 13, 2019
ffed8a0
Add CategoricalIndex test
Sep 14, 2019
504be90
Use isfinite
Sep 14, 2019
1290cb2
Fix
Sep 14, 2019
ab21763
Check TypeError as well for now
Sep 14, 2019
858ff06
Check error message
Sep 15, 2019
88874dc
Fix doc typo
Sep 15, 2019
eb76e1f
Revert "Use isfinite"
Sep 15, 2019
2a8186a
Extract array directly
Sep 15, 2019
afacbe3
Keep _maybe_promote
Sep 15, 2019
dbff36f
Add note
Sep 15, 2019
075ba33
Fix typo
Sep 15, 2019
5aeb8b6
Update doc/source/whatsnew/v1.0.0.rst
dsaxton Sep 16, 2019
af3ff15
Use np.asarray
Sep 16, 2019
e9cc1fa
Only check NaN
Sep 16, 2019
ab7b3ce
Change error message
Sep 17, 2019
754a3ed
Add to test cases
Sep 17, 2019
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3 changes: 3 additions & 0 deletions pandas/core/arrays/categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -520,6 +520,9 @@ def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
if dtype == self.dtype:
return self
return self._set_dtype(dtype)
if is_integer_dtype(dtype) and not np.isfinite(self.__array__()).all():
msg = "Cannot cast to int."
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ValueError: cannot convert float NaN to integer is what we do now on
pd.Series([1,2,np.nan],dtype='Int64').astype('int') so would replicate this message

raise ValueError(msg)
return np.array(self, dtype=dtype, copy=copy)

@cache_readonly
Expand Down
10 changes: 8 additions & 2 deletions pandas/tests/extension/test_categorical.py
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Expand Up @@ -19,7 +19,7 @@
import pytest

import pandas as pd
from pandas import Categorical
from pandas import Categorical, CategoricalIndex
from pandas.api.types import CategoricalDtype
from pandas.tests.extension import base
import pandas.util.testing as tm
Expand Down Expand Up @@ -197,7 +197,13 @@ def test_searchsorted(self, data_for_sorting):


class TestCasting(base.BaseCastingTests):
pass
@pytest.mark.parametrize("cls", [Categorical, CategoricalIndex])
@pytest.mark.parametrize("value", [np.nan, -np.inf, np.inf])
def test_cast_nan_to_int(self, cls, value):
s = cls([0, 1, value])

with pytest.raises((ValueError, TypeError)):
s.astype(int)


class TestArithmeticOps(base.BaseArithmeticOpsTests):
Expand Down