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Merged
merged 7 commits into from
Aug 18, 2023
Merged

Infer dtype of Series in more cases #766

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66ece55
Infer dtype of Series in more cases
twoertwein Aug 17, 2023
d495cb0
ignores
twoertwein Aug 17, 2023
4b87397
address some of the feedback
twoertwein Aug 18, 2023
a6b03aa
One of pandas's windows/linux inconsistencies
twoertwein Aug 18, 2023
76e302b
more changes; incl. np.intp/int64 -> np.integer
twoertwein Aug 18, 2023
e42d492
everything(?) but agg
twoertwein Aug 18, 2023
04752c4
return series
twoertwein Aug 18, 2023
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2 changes: 1 addition & 1 deletion pandas-stubs/core/frame.pyi
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Expand Up @@ -555,7 +555,7 @@ class DataFrame(NDFrame, OpsMixin):
@overload
def __getitem__( # type: ignore[misc]
self,
key: Series[_bool]
key: Series
| DataFrame
| Index
| np_ndarray_str
Expand Down
4 changes: 1 addition & 3 deletions pandas-stubs/core/indexes/period.pyi
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Expand Up @@ -6,9 +6,7 @@ import numpy as np
import pandas as pd
from pandas import Index
from pandas.core.indexes.accessors import PeriodIndexFieldOps
from pandas.core.indexes.datetimelike import (
DatetimeIndexOpsMixin as DatetimeIndexOpsMixin,
)
from pandas.core.indexes.datetimelike import DatetimeIndexOpsMixin
from pandas.core.indexes.timedeltas import TimedeltaIndex
from typing_extensions import Self

Expand Down
112 changes: 63 additions & 49 deletions pandas-stubs/core/series.pyi
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Expand Up @@ -211,46 +211,57 @@ class _LocIndexerSeries(_LocIndexer, Generic[S1]):
value: S1 | ArrayLike | Series[S1] | None,
) -> None: ...

_ListLike: TypeAlias = (
ArrayLike | dict[_str, np.ndarray] | Sequence[S1] | IndexOpsMixin[S1]
)

class Series(IndexOpsMixin[S1], NDFrame):
_ListLike: TypeAlias = ArrayLike | dict[_str, np.ndarray] | list | tuple | Index
__hash__: ClassVar[None]

# TODO: can __new__ be converted to __init__? Pandas implements __init__
@overload
def __new__(
def __new__( # type: ignore[misc]
cls,
data: DatetimeIndex | Sequence[Timestamp | np.datetime64 | datetime],
data: DatetimeIndex
| Sequence[np.datetime64 | datetime]
| np.datetime64
| datetime,
index: Axes | None = ...,
*,
dtype: TimestampDtypeArg = ...,
name: Hashable | None = ...,
name: Hashable = ...,
copy: bool = ...,
) -> TimestampSeries: ...
@overload
def __new__(
def __new__( # type: ignore[misc]
cls,
data: _ListLike,
index: Axes | None = ...,
*,
dtype: TimestampDtypeArg,
name: Hashable | None = ...,
name: Hashable = ...,
copy: bool = ...,
) -> TimestampSeries: ...
@overload
def __new__(
def __new__( # type: ignore[misc]
cls,
data: PeriodIndex,
index: Axes | None = ...,
*,
dtype: PeriodDtype = ...,
name: Hashable | None = ...,
name: Hashable = ...,
copy: bool = ...,
) -> PeriodSeries: ...
@overload
def __new__(
def __new__( # type: ignore[misc]
cls,
data: TimedeltaIndex | Sequence[Timedelta | np.timedelta64 | timedelta],
data: TimedeltaIndex
| Sequence[np.timedelta64 | timedelta]
| np.timedelta64
| timedelta,
index: Axes | None = ...,
*,
dtype: TimedeltaDtypeArg = ...,
name: Hashable | None = ...,
name: Hashable = ...,
copy: bool = ...,
) -> TimedeltaSeries: ...
@overload
Expand All @@ -260,35 +271,39 @@ class Series(IndexOpsMixin[S1], NDFrame):
| Interval[_OrderableT]
| Sequence[Interval[_OrderableT]],
index: Axes | None = ...,
*,
dtype: Literal["Interval"] = ...,
name: Hashable | None = ...,
name: Hashable = ...,
copy: bool = ...,
) -> IntervalSeries[_OrderableT]: ...
@overload
def __new__(
cls,
data: object | _ListLike | Series[S1] | dict[int, S1] | dict[_str, S1] | None,
dtype: type[S1],
data: Scalar | _ListLike | dict[int, Any] | dict[_str, Any] | None,
index: Axes | None = ...,
name: Hashable | None = ...,
*,
dtype: type[S1],
name: Hashable = ...,
copy: bool = ...,
) -> Self: ...
@overload
def __new__(
cls,
data: Series[S1] | dict[int, S1] | dict[_str, S1] = ...,
data: S1 | _ListLike[S1] | dict[int, S1] | dict[_str, S1],
index: Axes | None = ...,
*,
dtype: Dtype = ...,
name: Hashable | None = ...,
name: Hashable = ...,
copy: bool = ...,
) -> Self: ...
@overload
def __new__(
cls,
data: object | _ListLike | None = ...,
data: Scalar | _ListLike | dict[int, Any] | dict[_str, Any] | None = ...,
index: Axes | None = ...,
*,
dtype: Dtype = ...,
name: Hashable | None = ...,
name: Hashable = ...,
copy: bool = ...,
) -> Series: ...
@property
Expand Down Expand Up @@ -342,8 +357,8 @@ class Series(IndexOpsMixin[S1], NDFrame):
| Series[S1]
| slice
| MaskType
| tuple[S1 | slice, ...],
) -> Series: ...
| tuple[Hashable | slice, ...],
) -> Self: ...
@overload
def __getitem__(self, idx: int | _str) -> S1: ...
def __setitem__(self, key, value) -> None: ...
Expand Down Expand Up @@ -680,11 +695,13 @@ class Series(IndexOpsMixin[S1], NDFrame):
@overload
def dot(self, other: DataFrame) -> Series[S1]: ...
@overload
def dot(self, other: _ListLike) -> np.ndarray: ...
def dot(
self, other: ArrayLike | dict[_str, np.ndarray] | Sequence[S1] | Index[S1]
) -> np.ndarray: ...
def __matmul__(self, other): ...
def __rmatmul__(self, other): ...
@overload
def searchsorted(
def searchsorted( # type: ignore[misc]
self,
value: _ListLike,
side: Literal["left", "right"] = ...,
Expand Down Expand Up @@ -781,7 +798,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
ignore_index: _bool = ...,
inplace: Literal[False] = ...,
key: Callable | None = ...,
) -> Series: ...
) -> Self: ...
@overload
def sort_index(
self,
Expand Down Expand Up @@ -834,7 +851,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
axis: AxisIndex = ...,
*args,
**kwargs,
) -> Series[S1]: ...
) -> Self: ...
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Maybe make this Series since we really don't know the type of the Series - could be mix of int and float, or one, or the other

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Thank you, that made it work!

agg = aggregate
@overload
def transform(
Expand Down Expand Up @@ -902,7 +919,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
inplace: Literal[False] = ...,
level: Level | None = ...,
errors: IgnoreRaise = ...,
) -> Series: ...
) -> Self: ...
@overload
def rename(
self,
Expand All @@ -913,7 +930,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
inplace: Literal[False] = ...,
level: Level | None = ...,
errors: IgnoreRaise = ...,
) -> Series: ...
) -> Self: ...
@overload
def rename(
self,
Expand All @@ -932,7 +949,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
copy: _bool = ...,
limit: int | None = ...,
tolerance: float | None = ...,
) -> Series: ...
) -> Self: ...
@overload
def drop(
self,
Expand All @@ -956,7 +973,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
level: Level | None = ...,
inplace: Literal[False] = ...,
errors: IgnoreRaise = ...,
) -> Series: ...
) -> Self: ...
@overload
def drop(
self,
Expand Down Expand Up @@ -1344,7 +1361,7 @@ class Series(IndexOpsMixin[S1], NDFrame):
na_option: Literal["keep", "top", "bottom"] = ...,
ascending: _bool = ...,
pct: _bool = ...,
) -> Series: ...
) -> Series[float]: ...
def where(
self,
cond: Series[S1]
Expand Down Expand Up @@ -1431,14 +1448,10 @@ class Series(IndexOpsMixin[S1], NDFrame):
# just failed to generate these so I couldn't match
# them up.
@overload
def __add__(self, other: TimestampSeries) -> TimestampSeries: ...
@overload
def __add__(self, other: DatetimeIndex) -> TimestampSeries: ...
@overload
def __add__(self, other: Timestamp) -> TimestampSeries: ...
def __add__(self, other: S1 | Self) -> Self: ...
@overload
def __add__(
self, other: num | _str | Timedelta | _ListLike | Series[S1] | np.timedelta64
self, other: num | _str | Timedelta | _ListLike | Series | np.timedelta64
) -> Series: ...
# ignore needed for mypy as we want different results based on the arguments
@overload # type: ignore[override]
Expand Down Expand Up @@ -1479,7 +1492,10 @@ class Series(IndexOpsMixin[S1], NDFrame):
) -> Series[bool]: ...
@overload
def __or__(self, other: int | np_ndarray_anyint | Series[int]) -> Series[int]: ...
def __radd__(self, other: num | _str | _ListLike | Series[S1]) -> Series[S1]: ...
@overload
def __radd__(self, other: S1 | Series[S1]) -> Self: ...
@overload
def __radd__(self, other: num | _str | _ListLike | Series) -> Series: ...
# ignore needed for mypy as we want different results based on the arguments
@overload # type: ignore[override]
def __rand__( # type: ignore[misc]
Expand Down Expand Up @@ -1961,11 +1977,16 @@ class Series(IndexOpsMixin[S1], NDFrame):
axis: AxisIndex | None = ...,
copy: _bool = ...,
inplace: Literal[False] = ...,
) -> Series: ...
def set_axis(
self, labels, *, axis: Axis = ..., copy: _bool = ...
) -> Series[S1]: ...
) -> Self: ...
def set_axis(self, labels, *, axis: Axis = ..., copy: _bool = ...) -> Self: ...
def __iter__(self) -> Iterator[S1]: ...
def xs(
self,
key: Hashable,
axis: AxisIndex = ...,
level: Level | None = ...,
drop_level: _bool = ...,
) -> Self: ...

class TimestampSeries(Series[Timestamp]):
# ignore needed because of mypy
Expand Down Expand Up @@ -2092,13 +2113,6 @@ class TimedeltaSeries(Series[Timedelta]):
numeric_only: _bool = ...,
**kwargs,
) -> Timedelta: ...
def xs(
self,
key: Hashable,
axis: AxisIndex = ...,
level: Level | None = ...,
drop_level: _bool = ...,
) -> Series: ...

class PeriodSeries(Series[Period]):
# ignore needed because of mypy
Expand Down
2 changes: 1 addition & 1 deletion pyproject.toml
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Expand Up @@ -39,7 +39,7 @@ numpy = [
]

[tool.poetry.dev-dependencies]
mypy = "1.5.0"
mypy = "1.5.1"
pandas = "2.0.3"
pyarrow = ">=10.0.1"
pytest = ">=7.1.2"
Expand Down
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