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REF: Use np.result_type instead of np.find_common_type #53343

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merged 6 commits into from
May 23, 2023
Merged

REF: Use np.result_type instead of np.find_common_type #53343

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1f52516
REF: Use np.result_type instead of np.find_common_type
mroeschke May 22, 2023
7081bc1
Fall back to object
mroeschke May 22, 2023
cfb0522
Create a np_find_common_dtype
mroeschke May 22, 2023
a6d9ad3
Address circular import
mroeschke May 22, 2023
cfe1486
Use generator
mroeschke May 22, 2023
a0f176f
Typing
mroeschke May 22, 2023
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7 changes: 5 additions & 2 deletions pandas/core/algorithms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,10 @@
from pandas.util._decorators import doc
from pandas.util._exceptions import find_stack_level

from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
from pandas.core.dtypes.cast import (
construct_1d_object_array_from_listlike,
np_find_common_type,
)
from pandas.core.dtypes.common import (
ensure_float64,
ensure_object,
Expand Down Expand Up @@ -518,7 +521,7 @@ def f(c, v):
f = np.in1d

else:
common = np.find_common_type([values.dtype, comps_array.dtype], [])
common = np_find_common_type(values.dtype, comps_array.dtype)
values = values.astype(common, copy=False)
comps_array = comps_array.astype(common, copy=False)
f = htable.ismember
Expand Down
28 changes: 27 additions & 1 deletion pandas/core/dtypes/cast.py
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Expand Up @@ -1328,6 +1328,32 @@ def common_dtype_categorical_compat(
return dtype


def np_find_common_type(*dtypes: np.dtype) -> np.dtype:
"""
np.find_common_type implementation pre-1.25 deprecation using np.result_type
https://github.com/pandas-dev/pandas/pull/49569#issuecomment-1308300065

Parameters
----------
dtypes : np.dtypes

Returns
-------
np.dtype
"""
try:
common_dtype = np.result_type(*dtypes)
if common_dtype.kind in "mMSU":
# NumPy promotion currently (1.25) misbehaves for for times and strings,
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is there some numpy version at which we can remove this check?

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Not sure cc @seberg any thoughts?

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I have a PR that would fix it, so I hope next release this will happen. That was the PR which get stuck a bit on the discussion of what == should do.

# so fall back to object (find_common_dtype did unless there
# was only one dtype)
common_dtype = np.dtype("O")

except TypeError:
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can you give an example of what gets here?

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In [2]: np.result_type(np.dtype(float), np.dtype("M8"))
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[2], line 1
----> 1 np.result_type(np.dtype(float), np.dtype("M8"))

File <__array_function__ internals>:200, in result_type(*args, **kwargs)

TypeError: The DType <class 'numpy.dtype[float64]'> could not be promoted by <class 'numpy.dtype[datetime64]'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is `object`. The full list of DTypes is: (<class 'numpy.dtype[float64]'>, <class 'numpy.dtype[datetime64]'>)

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AFAICT pretty much anything that would resolve to object before would return a TypeError now

common_dtype = np.dtype("O")
return common_dtype


@overload
def find_common_type(types: list[np.dtype]) -> np.dtype:
...
Expand Down Expand Up @@ -1395,7 +1421,7 @@ def find_common_type(types):
if t.kind in "iufc":
return np.dtype("object")

return np.find_common_type(types, [])
return np_find_common_type(*types)


def construct_2d_arraylike_from_scalar(
Expand Down
9 changes: 4 additions & 5 deletions pandas/core/dtypes/concat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@
from pandas.core.dtypes.cast import (
common_dtype_categorical_compat,
find_common_type,
np_find_common_type,
)
from pandas.core.dtypes.dtypes import CategoricalDtype
from pandas.core.dtypes.generic import (
Expand Down Expand Up @@ -156,11 +157,9 @@ def _get_result_dtype(
target_dtype = np.dtype(object)
kinds = {"o"}
else:
# Argument 1 to "list" has incompatible type "Set[Union[ExtensionDtype,
# Any]]"; expected "Iterable[Union[dtype[Any], None, Type[Any],
# _SupportsDType[dtype[Any]], str, Tuple[Any, Union[SupportsIndex,
# Sequence[SupportsIndex]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
target_dtype = np.find_common_type(list(dtypes), []) # type: ignore[arg-type]
# error: Argument 1 to "np_find_common_type" has incompatible type
# "*Set[Union[ExtensionDtype, Any]]"; expected "dtype[Any]"
target_dtype = np_find_common_type(*dtypes) # type: ignore[arg-type]

return any_ea, kinds, target_dtype

Expand Down
6 changes: 4 additions & 2 deletions pandas/core/dtypes/dtypes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1921,6 +1921,8 @@ def _subtype_with_str(self):
def _get_common_dtype(self, dtypes: list[DtypeObj]) -> DtypeObj | None:
# TODO for now only handle SparseDtypes and numpy dtypes => extend
# with other compatible extension dtypes
from pandas.core.dtypes.cast import np_find_common_type

if any(
isinstance(x, ExtensionDtype) and not isinstance(x, SparseDtype)
for x in dtypes
Expand All @@ -1943,8 +1945,8 @@ def _get_common_dtype(self, dtypes: list[DtypeObj]) -> DtypeObj | None:
stacklevel=find_stack_level(),
)

np_dtypes = [x.subtype if isinstance(x, SparseDtype) else x for x in dtypes]
return SparseDtype(np.find_common_type(np_dtypes, []), fill_value=fill_value)
np_dtypes = (x.subtype if isinstance(x, SparseDtype) else x for x in dtypes)
return SparseDtype(np_find_common_type(*np_dtypes), fill_value=fill_value)


@register_extension_dtype
Expand Down
3 changes: 2 additions & 1 deletion pandas/core/internals/array_manager.py
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Expand Up @@ -29,6 +29,7 @@
ensure_dtype_can_hold_na,
find_common_type,
infer_dtype_from_scalar,
np_find_common_type,
)
from pandas.core.dtypes.common import (
ensure_platform_int,
Expand Down Expand Up @@ -1409,7 +1410,7 @@ def concat_arrays(to_concat: list) -> ArrayLike:
target_dtype = to_concat_no_proxy[0].dtype
elif all(x.kind in "iub" and isinstance(x, np.dtype) for x in dtypes):
# GH#42092
target_dtype = np.find_common_type(list(dtypes), [])
target_dtype = np_find_common_type(*dtypes)
else:
target_dtype = find_common_type([arr.dtype for arr in to_concat_no_proxy])

Expand Down
4 changes: 1 addition & 3 deletions pandas/tests/dtypes/test_inference.py
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Expand Up @@ -997,9 +997,7 @@ def test_maybe_convert_objects_itemsize(self, data0, data1):
data = [data0, data1]
arr = np.array(data, dtype="object")

common_kind = np.find_common_type(
[type(data0), type(data1)], scalar_types=[]
).kind
common_kind = np.result_type(type(data0), type(data1)).kind
kind0 = "python" if not hasattr(data0, "dtype") else data0.dtype.kind
kind1 = "python" if not hasattr(data1, "dtype") else data1.dtype.kind
if kind0 != "python" and kind1 != "python":
Expand Down