10000 [BUG] Sum of grouped bool has inconsistent dtype by rhshadrach · Pull Request #32894 · pandas-dev/pandas · GitHub
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[BUG] Sum of grouped bool has inconsistent dtype #32894

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Merged
merged 7 commits into from
Mar 26, 2020
Merged

[BUG] Sum of grouped bool has inconsistent dtype #32894

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465a69b
[BUG] Aggregated bool has inconsistent dtype
rhshadrach Mar 21, 2020
3bc35f8
Moved function groupby_result_dtype to _GroupBy._result_dtype
rhshadrach Mar 22, 2020
e6f2408
Moved cast functions to core.dtypes.cast, tests to test_aggregate
rhshadrach Mar 24, 2020
8902484
Added/improved docstrings and type hints
rhshadrach Mar 25, 2020
15028eb
Removed references to aggregation in docstrings.
rhshadrach Mar 25, 2020
3c484f3
Renamed try_cast_to_ea, updated comment, whatsnew
rhshadrach Mar 26, 2020
9b32d0e
Fixed import from refactor, restricted type in maybe_cast_to_extensio…
rhshadrach Mar 26, 2020
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Fixed import from refactor, restricted type in maybe_cast_to_extensio… 
…n_array
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@rhshadrach
rhshadrach committed Mar 26, 2020
commit 9b32d0eda7d2d25352d89e558557ef56243bc6a4
2 changes: 1 addition & 1 deletion pandas/core/arrays/base.py
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Expand Up @@ -1192,7 +1192,7 @@ def _maybe_convert(arr):
# https://github.com/pandas-dev/pandas/issues/22850
# We catch all regular exceptions here, and fall back
# to an ndarray.
res = maybe_cast_to_extension_array(self, arr)
res = maybe_cast_to_extension_array(type(self), arr)
if not isinstance(res, type(self)):
# exception raised in _from_sequence; ensure we have ndarray
res = np.asarray(arr)
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12 changes: 6 additions & 6 deletions pandas/core/arrays/categorical.py
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Expand Up @@ -19,7 +19,11 @@
)
from pandas.util._validators import validate_bool_kwarg, validate_fillna_kwargs

from pandas.core.dtypes.cast import coerce_indexer_dtype, maybe_infer_to_datetimelike
from pandas.core.dtypes.cast import (
coerce_indexer_dtype,
maybe_cast_to_extension_array,
maybe_infer_to_datetimelike,
)
from pandas.core.dtypes.common import (
ensure_int64,
ensure_object,
Expand Down Expand Up @@ -47,11 +51,7 @@
from pandas.core.accessor import PandasDelegate, delegate_names
import pandas.core.algorithms as algorithms
from pandas.core.algorithms import _get_data_algo, factorize, take, take_1d, unique1d
from pandas.core.arrays.base import (
ExtensionArray,
_extension_array_shared_docs,
maybe_cast_to_extension_array,
)
from pandas.core.arrays.base import ExtensionArray, _extension_array_shared_docs
from pandas.core.base import NoNewAttributesMixin, PandasObject, _shared_docs
import pandas.core.common as com
from pandas.core.construction import array, extract_array, sanitize_array
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7 changes: 4 additions & 3 deletions pandas/core/dtypes/cast.py
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Expand Up @@ -313,13 +313,13 @@ def maybe_cast_result_dtype(dtype: DtypeObj, how: str) -> DtypeObj:
return d.get((dtype, how), dtype)


def maybe_cast_to_extension_array(cls_or_instance, obj, dtype=None):
def maybe_cast_to_extension_array(cls, obj, dtype=None):
"""
Call to `_from_sequence` that returns the object unchanged on Exception.

Parameters
----------
cls_or_instance : ExtensionArray subclass or instance
cls : ExtensionArray subclass
obj : arraylike
Values to pass to cls._from_sequence
dtype : ExtensionDtype, optional
Expand All @@ -328,8 +328,9 @@ def maybe_cast_to_extension_array(cls_or_instance, obj, dtype=None):
-------
ExtensionArray or obj
"""
assert isinstance(cls, type), f"must pass a type: {cls}"
try:
result = cls_or_instance._from_sequence(obj, dtype=dtype)
result = cls._from_sequence(obj, dtype=dtype)
except Exception:
# We can't predict what downstream EA constructors may raise
result = obj
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2 changes: 1 addition & 1 deletion pandas/core/series.py
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Expand Up @@ -2725,7 +2725,7 @@ def combine(self, other, func, fill_value=None) -> "Series":
# TODO: can we do this for only SparseDtype?
# The function can return something of any type, so check
# if the type is compatible with the calling EA.
new_values = maybe_cast_to_extension_array(self._values, new_values)
new_values = maybe_cast_to_extension_array(type(self._values), new_values)
return self._constructor(new_values, index=new_index, name=new_name)

def combine_first(self, other) -> "Series":
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0