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TYP: resolve mypy ingores in core/indexing.py #47010

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Merged
merged 2 commits into from
May 25, 2022
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TYP: resolve mypy ingores in core/indexing.py #47010

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35dd7b5
TYP: resolve mypy ingores in core/indexing.py
iasoon May 12, 2022
1724c6e
Merge branch 'main' into typing/indexing
mroeschke May 25, 2022
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42 changes: 18 additions & 24 deletions pandas/core/indexing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -627,7 +627,7 @@ def iat(self) -> _iAtIndexer:

class _LocationIndexer(NDFrameIndexerBase):
_valid_types: str
axis = None
axis: int | None = None

@final
def __call__(self, axis=None):
Expand All @@ -652,7 +652,7 @@ def _get_setitem_indexer(self, key):
check_deprecated_indexers(x)

if self.axis is not None:
key = self._tupleize_axis_indexer(key)
key = _tupleize_axis_indexer(self.ndim, self.axis, key)

ax = self.obj._get_axis(0)

Expand Down Expand Up @@ -737,17 +737,6 @@ def _maybe_mask_setitem_value(self, indexer, value):

return indexer, value

@final
def _tupleize_axis_indexer(self, key) -> tuple:
"""
If we have an axis, adapt the given key to be axis-independent.
"""
new_key = [slice(None)] * self.ndim
# error: Invalid index type "Optional[Any]" for "List[slice]"; expected
# type "SupportsIndex"
new_key[self.axis] = key # type: ignore[index]
return tuple(new_key)

@final
def _ensure_listlike_indexer(self, key, axis=None, value=None):
"""
Expand Down Expand Up @@ -1621,7 +1610,7 @@ def _get_setitem_indexer(self, key):
key = list(key)

if self.axis is not None:
key = self._tupleize_axis_indexer(key)
key = _tupleize_axis_indexer(self.ndim, self.axis, key)

return key

Expand Down Expand Up @@ -2137,13 +2126,11 @@ def _ensure_iterable_column_indexer(self, column_indexer):
"""
Ensure that our column indexer is something that can be iterated over.
"""
ilocs: Sequence[int]
ilocs: Sequence[int] | np.ndarray
if is_integer(column_indexer):
ilocs = [column_indexer]
elif isinstance(column_indexer, slice):
ilocs = np.arange(len(self.obj.columns))[ # type: ignore[assignment]
column_indexer
]
ilocs = np.arange(len(self.obj.columns))[column_indexer]
elif isinstance(column_indexer, np.ndarray) and is_bool_dtype(
column_indexer.dtype
):
Expand Down Expand Up @@ -2201,18 +2188,16 @@ def ravel(i):
# TODO: This is hacky, align Series and DataFrame behavior GH#45778
if obj.ndim == 2 and is_empty_indexer(indexer[0]):
return ser._values.copy()
ser = ser.reindex(obj.axes[0][indexer[0]], copy=True)._values
ser_values = ser.reindex(obj.axes[0][indexer[0]], copy=True)._values

# single indexer
if len(indexer) > 1 and not multiindex_indexer:
len_indexer = len(indexer[1])
ser = (
np.tile(ser, len_indexer) # type: ignore[assignment]
.reshape(len_indexer, -1)
.T
ser_values = (
np.tile(ser_values, len_indexer).reshape(len_indexer, -1).T
)

return ser
return ser_values

for i, idx in enumerate(indexer):
ax = obj.axes[i]
Expand Down Expand Up @@ -2428,6 +2413,15 @@ def _tuplify(ndim: int, loc: Hashable) -> tuple[Hashable | slice, ...]:
return tuple(_tup)


def _tupleize_axis_indexer(ndim: int, axis: int, key) -> tuple:
"""
If we have an axis, adapt the given key to be axis-independent.
"""
new_key = [slice(None)] * ndim
new_key[axis] = key
return tuple(new_key)


def convert_to_index_sliceable(obj: DataFrame, key):
"""
If we are index sliceable, then return my slicer, otherwise return None.
Expand Down