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Fix annotations for DataFrame.apply() including additional overloads #448

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Merged
merged 5 commits into from
Dec 5, 2022
Merged

Fix annotations for DataFrame.apply() including additional overloads #448

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c2c1633
Fix annotations for DataFrame.apply() including additional overloads
gandhis1 Nov 26, 2022
2590294
Expand test suite and eliminate edge cases
gandhis1 Nov 26, 2022
40ab8f5
Cover all argument combinations and add a comprehensive set of test
gandhis1 Nov 26, 2022
6c2adb1
Try to remove unnecessary overloads
gandhis1 Nov 26, 2022
7338162
Refine the full set of overloads to cover value type of Series
gandhis1 Dec 4, 2022
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4 changes: 4 additions & 0 deletions pandas-stubs/_typing.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@ from typing import (
Iterator,
Literal,
Mapping,
MutableSequence,
Optional,
Protocol,
Sequence,
Expand Down Expand Up @@ -155,6 +156,9 @@ AxisType: TypeAlias = Literal["columns", "index", 0, 1]
DtypeNp = TypeVar("DtypeNp", bound=np.dtype[np.generic])
KeysArgType: TypeAlias = Any
ListLike = TypeVar("ListLike", Sequence, np.ndarray, "Series", "Index")
ListLikeExceptSeriesAndStr = TypeVar(
"ListLikeExceptSeriesAndStr", MutableSequence, np.ndarray, tuple, "Index"
)
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I agree, the name is awful, but do we have a better way to exclude str from list-likes?

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I don't know of any

ListLikeU: TypeAlias = Union[Sequence, np.ndarray, Series, Index]
StrLike: TypeAlias = Union[str, np.str_]
Scalar: TypeAlias = Union[
Expand Down
42 changes: 38 additions & 4 deletions pandas-stubs/core/frame.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -82,6 +82,7 @@ from pandas._typing import (
Label,
Level,
ListLike,
ListLikeExceptSeriesAndStr,
ListLikeU,
MaskType,
MergeHow,
Expand Down Expand Up @@ -1087,12 +1088,22 @@ class DataFrame(NDFrame, OpsMixin):
**kwargs,
) -> DataFrame: ...
@overload
def apply(
self,
f: Callable[..., ListLikeExceptSeriesAndStr],
axis: AxisType = ...,
raw: _bool = ...,
result_type: Literal[None] = ...,
args=...,
**kwargs,
) -> DataFrame: ...
@overload
def apply(
self,
f: Callable[..., Series],
axis: AxisType = ...,
raw: _bool = ...,
result_type: Literal["expand", "reduce", "broadcast"] | None = ...,
result_type: Literal[None] = ...,
args=...,
**kwargs,
) -> DataFrame: ...
Expand All @@ -1102,18 +1113,41 @@ class DataFrame(NDFrame, OpsMixin):
f: Callable[..., Scalar],
axis: AxisType = ...,
raw: _bool = ...,
result_type: Literal["expand", "reduce"] | None = ...,
result_type: Literal[None] = ...,
args=...,
**kwargs,
) -> Series: ...
@overload
def apply(
self,
f: Callable[..., Scalar],
result_type: Literal["broadcast"],
f: Callable[..., ListLikeExceptSeriesAndStr | Series | str | Scalar],
axis: AxisType = ...,
raw: _bool = ...,
args=...,
*,
result_type: Literal["reduce"],
**kwargs,
) -> Series: ...
@overload
def apply(
self,
f: Callable[..., ListLikeExceptSeriesAndStr | Series],
axis: AxisType = ...,
raw: _bool = ...,
args=...,
*,
result_type: Literal["expand"],
**kwargs,
) -> DataFrame: ...
@overload
def apply(
self,
f: Callable[..., ListLikeExceptSeriesAndStr | Series | str | Scalar],
axis: AxisType = ...,
raw: _bool = ...,
args=...,
*,
result_type: Literal["broadcast"],
**kwargs,
) -> DataFrame: ...
def applymap(
Expand Down
10 changes: 10 additions & 0 deletions tests/test_frame.py
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Expand Up @@ -486,6 +486,16 @@ def gethead(s: pd.Series, y: int) -> pd.Series:

check(assert_type(df.apply(gethead, args=(4,)), pd.DataFrame), pd.DataFrame)

def returns_tuple(x: pd.Series) -> tuple[str, str]:
return ("a", "b")

check(
assert_type(
df.apply(returns_tuple, axis=1, result_type="expand"), pd.DataFrame
),
pd.DataFrame,
)


def test_types_applymap() -> None:
df = pd.DataFrame(data={"col1": [2, 1], "col2": [3, 4]})
Expand Down