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ENH: Improve DataFrame loc indexing #138

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15 changes: 4 additions & 11 deletions pandas-stubs/core/frame.pyi
Original file line number Diff line number Diff line change
Expand Up @@ -138,17 +138,10 @@ class _LocIndexerFrame(_LocIndexer):
@overload
def __getitem__(
self,
idx: Union[int, StrLike],
) -> Series: ...
@overload
def __getitem__(
self,
idx: Tuple[Union[IndexType, MaskType], StrLike],
) -> Series: ...
@overload
def __getitem__(
self,
idx: Tuple[Tuple[slice, ...], StrLike],
idx: Union[
Union[ScalarT, None],
Tuple[Union[IndexType, MaskType, Tuple[slice, ...]], Union[ScalarT, None]],
],
) -> Series: ...
@overload
def __setitem__(
Expand Down
73 changes: 71 additions & 2 deletions tests/test_frame.py
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
# flake8: noqa: F841
from datetime import date
import datetime
import io
from pathlib import Path
import tempfile
Expand Down Expand Up @@ -943,7 +943,7 @@ def test_types_regressions() -> None:
ss2: pd.Series = pd.concat([s1, s2])

# https://github.com/microsoft/python-type-stubs/issues/110
d: date = pd.Timestamp("2021-01-01")
d: datetime.date = pd.Timestamp("2021-01-01")
tslist: List[pd.Timestamp] = list(pd.to_datetime(["2022-01-01", "2022-01-02"]))
sseries: pd.Series = pd.Series(tslist)
sseries_plus1: pd.Series = sseries + pd.Timedelta(1, "d")
Expand Down Expand Up @@ -1180,3 +1180,72 @@ def test_columns_mixlist() -> None:
key: List[Union[int, str]]
key = [1]
check(assert_type(df[key], pd.DataFrame), pd.DataFrame)


def test_frame_scalars_slice() -> None:
# GH 133
# scalars:
# str, bytes, datetime.date, datetime.datetime, datetime.timedelta, bool, int,
# float, complex, Timestamp, Timedelta

str_ = "a"
bytes_ = b"7"
date = datetime.date(1999, 12, 31)
datetime_ = datetime.datetime(1999, 12, 31)
timedelta = datetime.datetime(2000, 1, 1) - datetime.datetime(1999, 12, 31)
bool_ = True
int_ = 2
float_ = 3.14
complex_ = 1.0 + 3.0j
timestamp = pd.Timestamp(0)
pd_timedelta = pd.Timedelta(0, unit="D")
none = None
idx = [
str_,
bytes_,
date,
datetime_,
timedelta,
bool_,
int_,
float_,
complex_,
timestamp,
pd_timedelta,
none,
]
values = np.arange(len(idx))[:, None] + np.arange(len(idx))
df = pd.DataFrame(values, columns=idx, index=idx)

# Note: bool_ cannot be tested since the index is object and pandas does not
# support boolean access using loc except when the index is boolean
check(assert_type(df.loc[str_], pd.Series), pd.Series)
check(assert_type(df.loc[bytes_], pd.Series), pd.Series)
check(assert_type(df.loc[date], pd.Series), pd.Series)
check(assert_type(df.loc[datetime_], pd.Series), pd.Series)
check(assert_type(df.loc[timedelta], pd.Series), pd.Series)
check(assert_type(df.loc[int_], pd.Series), pd.Series)
check(assert_type(df.loc[float_], pd.Series), pd.Series)
check(assert_type(df.loc[complex_], pd.Series), pd.Series)
check(assert_type(df.loc[timestamp], pd.Series), pd.Series)
check(assert_type(df.loc[pd_timedelta], pd.Series), pd.Series)
check(assert_type(df.loc[none], pd.Series), pd.Series)

check(assert_type(df.loc[:, str_], pd.Series), pd.Series)
check(assert_type(df.loc[:, bytes_], pd.Series), pd.Series)
check(assert_type(df.loc[:, date], pd.Series), pd.Series)
check(assert_type(df.loc[:, datetime_], pd.Series), pd.Series)
check(assert_type(df.loc[:, timedelta], pd.Series), pd.Series)
check(assert_type(df.loc[:, int_], pd.Series), pd.Series)
check(assert_type(df.loc[:, float_], pd.Series), pd.Series)
check(assert_type(df.loc[:, complex_], pd.Series), pd.Series)
check(assert_type(df.loc[:, timestamp], pd.Series), pd.Series)
check(assert_type(df.loc[:, pd_timedelta], pd.Series), pd.Series)
check(assert_type(df.loc[:, none], pd.Series), pd.Series)


def test_boolean_loc() -> None:
# Booleans can only be used in loc when the index is boolean
df = pd.DataFrame([[0, 1], [1, 0]], columns=[True, False], index=[True, False])
check(assert_type(df.loc[True], pd.Series), pd.Series)
check(assert_type(df.loc[:, False], pd.Series), pd.Series)