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TYP: to_numpy #41751

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2 changes: 1 addition & 1 deletion pandas/core/array_algos/putmask.py
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Expand Up @@ -191,7 +191,7 @@ def extract_bool_array(mask: ArrayLike) -> np.ndarray:
# We could have BooleanArray, Sparse[bool], ...
# Except for BooleanArray, this is equivalent to just
# np.asarray(mask, dtype=bool)
mask = mask.to_numpy(dtype=bool, na_value=False)
mask = mask.to_numpy(dtype=np.dtype("bool"), na_value=False)
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this shouldn't need to be changed. Not sure without checking when the NpDtype alias was added, but pretty sure from memory that this is causing several issues (e.g. #41203 (review)) and needs to be fixed first. #41185

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either way i guess. at some point it is going to be cast to a np.dtype object, so i see it as harmless

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yes, but the change means that the to_numpy annotation is wrong and since it's public will give false positives to users.


mask = np.asarray(mask, dtype=bool)
return mask
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10 changes: 3 additions & 7 deletions pandas/core/arrays/base.py
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Expand Up @@ -26,6 +26,7 @@
ArrayLike,
Dtype,
FillnaOptions,
NpDtype,
PositionalIndexer,
Shape,
)
Expand Down Expand Up @@ -429,7 +430,7 @@ def __ne__(self, other: Any) -> ArrayLike: # type: ignore[override]

def to_numpy(
self,
dtype: Dtype | None = None,
dtype: NpDtype | None = None,
copy: bool = False,
na_value=lib.no_default,
) -> np.ndarray:
Expand Down Expand Up @@ -458,12 +459,7 @@ def to_numpy(
-------
numpy.ndarray
"""
# error: Argument "dtype" to "asarray" has incompatible type
# "Union[ExtensionDtype, str, dtype[Any], Type[str], Type[float], Type[int],
# Type[complex], Type[bool], Type[object], None]"; expected "Union[dtype[Any],
# None, type, _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any, Union[int,
# Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
result = np.asarray(self, dtype=dtype) # type: ignore[arg-type]
result = np.asarray(self, dtype=dtype)
if copy or na_value is not lib.no_default:
result = result.copy()
if na_value is not lib.no_default:
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5 changes: 1 addition & 4 deletions pandas/core/arrays/masked.py
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Expand Up @@ -208,10 +208,7 @@ def __len__(self) -> int:
def __invert__(self: BaseMaskedArrayT) -> BaseMaskedArrayT:
return type(self)(~self._data, self._mask.copy())

# error: Argument 1 of "to_numpy" is incompatible with supertype "ExtensionArray";
# supertype defines the argument type as "Union[ExtensionDtype, str, dtype[Any],
# Type[str], Type[float], Type[int], Type[complex], Type[bool], Type[object], None]"
def to_numpy( # type: ignore[override]
def to_numpy(
self,
dtype: NpDtype | None = None,
copy: bool = False,
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5 changes: 1 addition & 4 deletions pandas/core/arrays/numpy_.py
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Expand Up @@ -367,10 +367,7 @@ def skew(
# ------------------------------------------------------------------------
# Additional Methods

# error: Argument 1 of "to_numpy" is incompatible with supertype "ExtensionArray";
# supertype defines the argument type as "Union[ExtensionDtype, str, dtype[Any],
# Type[str], Type[float], Type[int], Type[complex], Type[bool], Type[object], None]"
def to_numpy( # type: ignore[override]
def to_numpy(
self,
dtype: NpDtype | None = None,
copy: bool = False,
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5 changes: 1 addition & 4 deletions pandas/core/arrays/string_arrow.py
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Expand Up @@ -275,10 +275,7 @@ def __arrow_array__(self, type=None):
"""Convert myself to a pyarrow Array or ChunkedArray."""
return self._data

# error: Argument 1 of "to_numpy" is incompatible with supertype "ExtensionArray";
# supertype defines the argument type as "Union[ExtensionDtype, str, dtype[Any],
# Type[str], Type[float], Type[int], Type[complex], Type[bool], Type[object], None]"
def to_numpy( # type: ignore[override]
def to_numpy(
self,
dtype: NpDtype | None = None,
copy: bool = False,
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11 changes: 3 additions & 8 deletions pandas/core/base.py
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Expand Up @@ -19,10 +19,10 @@
import pandas._libs.lib as lib
from pandas._typing import (
ArrayLike,
Dtype,
DtypeObj,
FrameOrSeries,
IndexLabel,
NpDtype,
Shape,
final,
)
Expand Down Expand Up @@ -413,7 +413,7 @@ def array(self) -> ExtensionArray:

def to_numpy(
self,
dtype: Dtype | None = None,
dtype: NpDtype | None = None,
copy: bool = False,
na_value=lib.no_default,
**kwargs,
Expand Down Expand Up @@ -523,12 +523,7 @@ def to_numpy(
f"to_numpy() got an unexpected keyword argument '{bad_keys}'"
)

# error: Argument "dtype" to "asarray" has incompatible type
# "Union[ExtensionDtype, str, dtype[Any], Type[str], Type[float], Type[int],
# Type[complex], Type[bool], Type[object], None]"; expected "Union[dtype[Any],
# None, type, _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any, Union[int,
# Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
result = np.asarray(self._values, dtype=dtype) # type: ignore[arg-type]
result = np.asarray(self._values, dtype=dtype)
# TODO(GH-24345): Avoid potential double copy
if copy or na_value is not lib.no_default:
result = result.copy()
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4 changes: 2 additions & 2 deletions pandas/core/groupby/groupby.py
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Expand Up @@ -2424,12 +2424,12 @@ def pre_processor(vals: ArrayLike) -> tuple[np.ndarray, np.dtype | None]:
inference: np.dtype | None = None
if is_integer_dtype(vals.dtype):
if isinstance(vals, ExtensionArray):
out = vals.to_numpy(dtype=float, na_value=np.nan)
out = vals.to_numpy(dtype="float64", na_value=np.nan)
else:
out = vals
inference = np.dtype(np.int64)
elif is_bool_dtype(vals.dtype) and isinstance(vals, ExtensionArray):
out = vals.to_numpy(dtype=float, na_value=np.nan)
out = vals.to_numpy(dtype="float64", na_value=np.nan)
elif is_datetime64_dtype(vals.dtype):
inference = np.dtype("datetime64[ns]")
out = np.asarray(vals).astype(float)
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26 changes: 8 additions & 18 deletions pandas/core/internals/managers.py
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Expand Up @@ -24,6 +24,7 @@
ArrayLike,
Dtype,
DtypeObj,
NpDtype,
Shape,
type_t,
)
Expand Down Expand Up @@ -1385,7 +1386,7 @@ def to_dict(self, copy: bool = True):
def as_array(
self,
transpose: bool = False,
dtype: Dtype | None = None,
dtype: NpDtype | None = None,
copy: bool = False,
na_value=lib.no_default,
) -> np.ndarray:
Expand All @@ -1396,7 +1397,7 @@ def as_array(
----------
transpose : bool, default False
If True, transpose the return array.
dtype : object, default None
dtype : str or numpy.dtype, optional
Data type of the return array.
copy : bool, default False
If True then guarantee that a copy is returned. A value of
Expand Down Expand Up @@ -1430,12 +1431,7 @@ def as_array(
else:
arr = np.asarray(blk.get_values())
if dtype:
# error: Argument 1 to "astype" of "_ArrayOrScalarCommon" has
# incompatible type "Union[ExtensionDtype, str, dtype[Any],
# Type[object]]"; expected "Union[dtype[Any], None, type,
# _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any, Union[int,
# Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
arr = arr.astype(dtype, copy=False) # type: ignore[arg-type]
arr = arr.astype(dtype, copy=False)
else:
arr = self._interleave(dtype=dtype, na_value=na_value)
# The underlying data was copied within _interleave
Expand Down Expand Up @@ -1468,12 +1464,9 @@ def _interleave(
elif is_dtype_equal(dtype, str):
dtype = np.dtype("object")

# error: Argument "dtype" to "empty" has incompatible type
# "Union[ExtensionDtype, str, dtype[Any], Type[object], None]"; expected
# "Union[dtype[Any], None, type, _SupportsDType, str, Union[Tuple[Any, int],
# Tuple[Any, Union[int, Sequence[int]]], List[Any], _DTypeDict,
# Tuple[Any, Any]]]"
result = np.empty(self.shape, dtype=dtype) # type: ignore[arg-type]
dtype = cast(np.dtype, dtype)

result = np.empty(self.shape, dtype=dtype)

itemmask = np.zeros(self.shape[0])

Expand All @@ -1488,10 +1481,7 @@ def _interleave(
dtype=dtype, na_value=na_value
)
else:
# error: Argument 1 to "get_values" of "Block" has incompatible type
# "Union[ExtensionDtype, str, dtype[Any], Type[object], None]"; expected
# "Union[dtype[Any], ExtensionDtype, None]"
arr = blk.get_values(dtype) # type: ignore[arg-type]
arr = blk.get_values(dtype)
result[rl.indexer] = arr
itemmask[rl.indexer] = 1

Expand Down