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Set correct missing value indicator in astype for categorical #45012

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Merged
merged 6 commits into from
Dec 28, 2021
Merged

Set correct missing value indicator in astype for categorical #45012

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d59dcd3
Set correct missing value indicator in astype for categorical
phofl Dec 22, 2021
f4e8c9b
Try casting twice
phofl Dec 22, 2021
c21fdcf
Check if fill value is valid
phofl Dec 22, 2021
afacccb
Catch np string dtype
phofl Dec 22, 2021
7b5619f
Add comment
phofl Dec 28, 2021
3991976
Add dtypes to module level
phofl Dec 28, 2021
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12 changes: 6 additions & 6 deletions pandas/core/arrays/categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -108,7 +108,6 @@
)
import pandas.core.common as com
from pandas.core.construction import (
ensure_wrapped_if_datetimelike,
extract_array,
sanitize_array,
)
Expand Down Expand Up @@ -539,14 +538,15 @@ def astype(self, dtype: AstypeArg, copy: bool = True) -> ArrayLike:

else:
# GH8628 (PERF): astype category codes instead of astyping array
if is_datetime64_dtype(self.categories):
new_cats = ensure_wrapped_if_datetimelike(self.categories._values)
else:
new_cats = np.asarray(self.categories)
new_cats = self.categories._values

try:
new_cats = new_cats.astype(dtype=dtype, copy=copy)
fill_value = lib.item_from_zerodim(np.array(np.nan).astype(dtype))
fill_value = self.categories._na_value
if not is_valid_na_for_dtype(fill_value, dtype):
fill_value = lib.item_from_zerodim(
np.array(self.categories._na_value).astype(dtype)
)
except (
TypeError, # downstream error msg for CategoricalIndex is misleading
ValueError,
Expand Down
8 changes: 7 additions & 1 deletion pandas/core/dtypes/missing.py
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Expand Up @@ -56,6 +56,8 @@

nan_checker = np.isnan
INF_AS_NA = False
_dtype_object = np.dtype("object")
_dtype_str = np.dtype(str)


def isna(obj):
Expand Down Expand Up @@ -640,7 +642,11 @@ def is_valid_na_for_dtype(obj, dtype: DtypeObj) -> bool:
# Numeric
return obj is not NaT and not isinstance(obj, (np.datetime64, np.timedelta64))

elif dtype == np.dtype("object"):
elif dtype == _dtype_str:
# numpy string dtypes to avoid float np.nan
return not isinstance(obj, (np.datetime64, np.timedelta64, Decimal, float))

elif dtype == _dtype_object:
# This is needed for Categorical, but is kind of weird
return True

Expand Down
2 changes: 1 addition & 1 deletion pandas/tests/arrays/categorical/test_dtypes.py
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Expand Up @@ -182,7 +182,7 @@ def test_astype_object_datetime_categories(self):
# GH#40754
cat = Categorical(to_datetime(["2021-03-27", NaT]))
result = cat.astype(object)
expected = np.array([Timestamp("2021-03-27 00:00:00"), np.nan], dtype="object")
expected = np.array([Timestamp("2021-03-27 00:00:00"), NaT], dtype="object")
tm.assert_numpy_array_equal(result, expected)

def test_astype_object_timestamp_categories(self):
Expand Down