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8 files changed

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-233
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8 files changed

+295
-233
lines changed

‎pandas-stubs/_typing.pyi‎

Lines changed: 5 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -317,10 +317,7 @@ BuiltinFloatDtypeArg: TypeAlias = type[float] | Literal["float"]
317317
PandasFloatDtypeArg: TypeAlias = (
318318
pd.Float32Dtype | pd.Float64Dtype | Literal["Float32", "Float64"]
319319
)
320-
PandasAstypeFloatDtypeArg: TypeAlias = (
321-
Literal["float_"] # noqa: PYI030
322-
| Literal["f16", "float128", "longdouble", "longfloat"]
323-
)
320+
PandasAstypeFloatDtypeArg: TypeAlias = Literal["float_", "longdouble", "longfloat"]
324321
# Numpy float types and their string aliases
325322
NumpyFloatDtypeArg: TypeAlias = (
326323
# NOTE: Alias np.float16 only on Linux x86_64, use np.half instead
@@ -335,7 +332,7 @@ NumpyFloatDtypeArg: TypeAlias = (
335332
| Literal["d", "f8", "float64", "double"]
336333
# https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.longdouble
337334
| type[np.longdouble]
338-
| Literal["g"] # "float128"
335+
| Literal["g", "f16", "float128"]
339336
)
340337
# PyArrow floating point types and their string aliases
341338
PyArrowFloatDtypeArg: TypeAlias = Literal[
@@ -348,7 +345,6 @@ PyArrowFloatDtypeArg: TypeAlias = Literal[
348345
FloatDtypeArg: TypeAlias = (
349346
BuiltinFloatDtypeArg
350347
| PandasFloatDtypeArg
351-
| PandasAstypeFloatDtypeArg
352348
| NumpyFloatDtypeArg
353349
| PyArrowFloatDtypeArg
354350
)
@@ -372,9 +368,7 @@ NumpyComplexDtypeArg: TypeAlias = (
372368
| type[np.clongdouble]
373369
| Literal["G", "clongdouble"]
374370
)
375-
ComplexDtypeArg: TypeAlias = (
376-
BuiltinComplexDtypeArg | PandasAstypeComplexDtypeArg | NumpyComplexDtypeArg
377-
)
371+
ComplexDtypeArg: TypeAlias = BuiltinComplexDtypeArg | NumpyComplexDtypeArg
378372
PandasAstypeTimedeltaDtypeArg: TypeAlias = Literal[
379373
"timedelta64[Y]",
380374
"timedelta64[M]",
@@ -433,9 +427,7 @@ PyArrowTimedeltaDtypeArg: TypeAlias = Literal[
433427
"duration[us][pyarrow]",
434428
"duration[ns][pyarrow]",
435429
]
436-
TimedeltaDtypeArg: TypeAlias = (
437-
PandasAstypeTimedeltaDtypeArg | NumpyTimedeltaDtypeArg | PyArrowTimedeltaDtypeArg
438-
)
430+
TimedeltaDtypeArg: TypeAlias = NumpyTimedeltaDtypeArg | PyArrowTimedeltaDtypeArg
439431
# Pandas timestamp type and its string alias
440432
# Not comprehensive
441433
PandasTimestampDtypeArg: TypeAlias = (
@@ -509,10 +501,7 @@ PyArrowTimestampDtypeArg: TypeAlias = Literal[
509501
"timestamp[ns][pyarrow]",
510502
]
511503
TimestampDtypeArg: TypeAlias = (
512-
PandasTimestampDtypeArg
513-
| PandasAstypeTimestampDtypeArg
514-
| NumpyTimestampDtypeArg
515-
| PyArrowTimestampDtypeArg
504+
PandasTimestampDtypeArg | NumpyTimestampDtypeArg | PyArrowTimestampDtypeArg
516505
)
517506
# Builtin str type and its string alias
518507
BuiltinStrDtypeArg: TypeAlias = type[str] | Literal["str"]

‎pandas-stubs/core/series.pyi‎

Lines changed: 75 additions & 87 deletions
Original file line numberDiff line numberDiff line change
@@ -48,7 +48,6 @@ from matplotlib.axes import (
4848
SubplotBase,
4949
)
5050
import numpy as np
51-
from numpy import typing as npt
5251
from pandas import (
5352
Index,
5453
Period,
@@ -63,12 +62,15 @@ from pandas.core.api import (
6362
Int64Dtype as Int64Dtype,
6463
)
6564
from pandas.core.arrays.base import ExtensionArray
66-
from pandas.core.arrays.boolean import BooleanDtype
65+
from pandas.core.arrays.boolean import (
66+
BooleanDtype,
67+
)
6768
from pandas.core.arrays.categorical import (
6869
Categorical,
6970
CategoricalAccessor,
7071
)
7172
from pandas.core.arrays.datetimes import DatetimeArray
73+
from pandas.core.arrays.floating import FloatingArray
7274
from pandas.core.arrays.timedeltas import TimedeltaArray
7375
from pandas.core.base import (
7476
ArrayIndexSeriesTimedeltaNoSeq,
@@ -190,6 +192,10 @@ from pandas._typing import (
190192
NaPosition,
191193
NsmallestNlargestKeep,
192194
ObjectDtypeArg,
195+
PandasAstypeComplexDtypeArg,
196+
PandasAstypeFloatDtypeArg,
197+
PandasAstypeTimedeltaDtypeArg,
198+
PandasAstypeTimestampDtypeArg,
193199
PeriodFrequency,
194200
QuantileInterpolation,
195201
RandomState,
@@ -343,41 +349,32 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
343349
__index__: ClassVar[None]
344350
__hash__: ClassVar[None] # pyright: ignore[reportIncompatibleMethodOverride]
345351

346-
@overload
347-
def __new__(
348-
cls,
349-
data: npt.NDArray[np.float64],
350-
index: AxesData | None = ...,
351-
dtype: Dtype = ...,
352-
name: Hashable = ...,
353-
copy: bool = ...,
354-
) -> Series[float]: ...
355352
@overload
356353
def __new__(
357354
cls,
358355
data: Sequence[Never],
359-
index: AxesData | None = ...,
360-
dtype: Dtype = ...,
361-
name: Hashable = ...,
362-
copy: bool = ...,
356+
index: AxesData | None = None,
357+
dtype: None = None,
358+
name: Hashable = None,
359+
copy: bool | None = None,
363360
) -> Series: ...
364361
@overload
365362
def __new__(
366363
cls,
367364
data: Sequence[list[_str]],
368-
index: AxesData | None = ...,
369-
dtype: Dtype = ...,
370-
name: Hashable = ...,
371-
copy: bool = ...,
365+
index: AxesData | None = None,
366+
dtype: None = None,
367+
name: Hashable = None,
368+
copy: bool | None = None,
372369
) -> Series[list[_str]]: ...
373370
@overload
374371
def __new__(
375372
cls,
376373
data: Sequence[_str],
377-
index: AxesData | None = ...,
378-
dtype: Dtype = ...,
379-
name: Hashable = ...,
380-
copy: bool = ...,
374+
index: AxesData | None = None,
375+
dtype: Dtype | None = None,
376+
name: Hashable = None,
377+
copy: bool | None = None,
381378
) -> Series[_str]: ...
382379
@overload
383380
def __new__(
@@ -390,48 +387,48 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
390387
| datetime
391388
| date
392389
),
393-
index: AxesData | None = ...,
390+
index: AxesData | None = None,
394391
dtype: TimestampDtypeArg = ...,
395-
name: Hashable = ...,
396-
copy: bool = ...,
392+
name: Hashable = None,
393+
copy: bool | None = None,
397394
) -> Series[Timestamp]: ...
398395
@overload
399396
def __new__(
400397
cls,
401-
data: _DataLike,
402-
index: AxesData | None = ...,
398+
data: Sequence[datetime | np.timedelta64] | np_ndarray_dt | DatetimeArray,
399+
index: AxesData | None = None,
403400
*,
404401
dtype: TimestampDtypeArg,
405-
name: Hashable = ...,
406-
copy: bool = ...,
402+
name: Hashable = None,
403+
copy: bool | None = None,
407404
) -> Series[Timestamp]: ...
408405
@overload
409406
def __new__(
410407
cls,
411408
data: _DataLike,
412-
index: AxesData | None = ...,
409+
index: AxesData | None = None,
413410
*,
414411
dtype: CategoryDtypeArg,
415-
name: Hashable = ...,
416-
copy: bool = ...,
412+
name: Hashable = None,
413+
copy: bool | None = None,
417414
) -> Series[CategoricalDtype]: ...
418415
@overload
419416
def __new__(
420417
cls,
421418
data: PeriodIndex | Sequence[Period],
422-
index: AxesData | None = ...,
419+
index: AxesData | None = None,
423420
dtype: PeriodDtype = ...,
424-
name: Hashable = ...,
425-
copy: bool = ...,
421+
name: Hashable = None,
422+
copy: bool | None = None,
426423
) -> Series[Period]: ...
427424
@overload
428425
def __new__(
429426
cls,
430427
data: Sequence[BaseOffset],
431-
index: AxesData | None = ...,
428+
index: AxesData | None = None,
432429
dtype: PeriodDtype = ...,
433-
name: Hashable = ...,
434-
copy: bool = ...,
430+
name: Hashable = None,
431+
copy: bool | None = None,
435432
) -> Series[BaseOffset]: ...
436433
@overload
437434
def __new__(
@@ -443,10 +440,10 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
443440
| np.timedelta64
444441
| timedelta
445442
),
446-
index: AxesData | None = ...,
443+
index: AxesData | None = None,
447444
dtype: TimedeltaDtypeArg = ...,
448-
name: Hashable = ...,
449-
copy: bool = ...,
445+
name: Hashable = None,
446+
copy: bool | None = None,
450447
) -> Series[Timedelta]: ...
451448
@overload
452449
def __new__(
@@ -457,67 +454,58 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
457454
| Sequence[Interval[_OrderableT]]
458455
| dict[HashableT1, Interval[_OrderableT]]
459456
),
460-
index: AxesData | None = ...,
457+
index: AxesData | None = None,
461458
dtype: Literal["Interval"] = ...,
462-
name: Hashable = ...,
463-
copy: bool = ...,
459+
name: Hashable = None,
460+
copy: bool | None = None,
464461
) -> Series[Interval[_OrderableT]]: ...
465462
@overload
466463
def __new__( # type: ignore[overload-overlap]
467464
cls,
468465
data: Scalar | _DataLike | dict[HashableT1, Any] | None,
469-
index: AxesData | None = ...,
466+
index: AxesData | None = None,
470467
*,
471468
dtype: type[S1],
472-
name: Hashable = ...,
473-
copy: bool = ...,
469+
name: Hashable = None,
470+
copy: bool | None = None,
474471
) -> Self: ...
475472
@overload
476-
def __new__( # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
473+
def __new__( # pyright: ignore[reportOverlappingOverload]
477474
cls,
478-
data: Sequence[bool],
479-
index: AxesData | None = ...,
480-
dtype: Dtype = ...,
481-
name: Hashable = ...,
482-
copy: bool = ...,
475+
data: Sequence[bool | np.bool],
476+
index: AxesData | None = None,
477+
dtype: Dtype | None = None,
478+
name: Hashable = None,
479+
copy: bool | None = None,
483480
) -> Series[bool]: ...
484481
@overload
485-
def __new__( # type: ignore[overload-overlap]
482+
def __new__(
486483
cls,
487-
data: Sequence[int],
488-
index: AxesData | None = ...,
489-
dtype: Dtype = ...,
490-
name: Hashable = ...,
491-
copy: bool = ...,
484+
data: Sequence[int | np.integer],
485+
index: AxesData | None = None,
486+
dtype: Dtype | None = None,
487+
name: Hashable = None,
488+
copy: bool | None = None,
492489
) -> Series[int]: ...
493490
@overload
494491
def __new__(
495492
cls,
496-
data: Sequence[float],
497-
index: AxesData | None = ...,
498-
dtype: Dtype = ...,
499-
name: Hashable = ...,
500-
copy: bool = ...,
501-
) -> Series[float]: ...
502-
@overload
503-
def __new__( # type: ignore[overload-cannot-match] # pyright: ignore[reportOverlappingOverload]
504-
cls,
505-
data: Sequence[int | float],
506-
index: AxesData | None = ...,
507-
dtype: Dtype = ...,
508-
name: Hashable = ...,
509-
copy: bool = ...,
493+
data: Sequence[float | np.floating] | np_ndarray_float | FloatingArray,
494+
index: AxesData | None = None,
495+
dtype: FloatDtypeArg | None = None,
496+
name: Hashable = None,
497+
copy: bool | None = None,
510498
) -> Series[float]: ...
511499
@overload
512500
def __new__(
513501
cls,
514502
data: (
515503
S1 | _DataLikeS1[S1] | dict[HashableT1, S1] | KeysView[S1] | ValuesView[S1]
516504
),
517-
index: AxesData | None = ...,
518-
dtype: Dtype = ...,
519-
name: Hashable = ...,
520-
copy: bool = ...,
505+
index: AxesData | None = None,
506+
dtype: Dtype | None = None,
507+
name: Hashable = None,
508+
copy: bool | None = None,
521509
) -> Self: ...
522510
@overload
523511
def __new__(
@@ -530,11 +518,11 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
530518
| NaTType
531519
| NAType
532520
| None
533-
) = ...,
534-
index: AxesData | None = ...,
535-
dtype: Dtype = ...,
536-
name: Hashable = ...,
537-
copy: bool = ...,
521+
) = None,
522+
index: AxesData | None = None,
523+
dtype: Dtype | None = None,
524+
name: Hashable = None,
525+
copy: bool | None = None,
538526
) -> Series: ...
539527
@property
540528
def hasnans(self) -> bool: ...
@@ -1446,28 +1434,28 @@ class Series(IndexOpsMixin[S1], ElementOpsMixin[S1], NDFrame):
14461434
@overload
14471435
def astype(
14481436
self,
1449-
dtype: FloatDtypeArg,
1437+
dtype: FloatDtypeArg | PandasAstypeFloatDtypeArg,
14501438
copy: _bool = ...,
14511439
errors: IgnoreRaise = ...,
14521440
) -> Series[float]: ...
14531441
@overload
14541442
def astype(
14551443
self,
1456-
dtype: ComplexDtypeArg,
1444+
dtype: ComplexDtypeArg | PandasAstypeComplexDtypeArg,
14571445
copy: _bool = ...,
14581446
errors: IgnoreRaise = ...,
14591447
) -> Series[complex]: ...
14601448
@overload
14611449
def astype(
14621450
self,
1463-
dtype: TimedeltaDtypeArg,
1451+
dtype: TimedeltaDtypeArg | PandasAstypeTimedeltaDtypeArg,
14641452
copy: _bool = ...,
14651453
errors: IgnoreRaise = ...,
14661454
) -> Series[Timedelta]: ...
14671455
@overload
14681456
def astype(
14691457
self,
1470-
dtype: TimestampDtypeArg,
1458+
dtype: TimestampDtypeArg | PandasAstypeTimestampDtypeArg,
14711459
copy: _bool = ...,
14721460
errors: IgnoreRaise = ...,
14731461
) -> Series[Timestamp]: ...

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