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STY: ignore mypy errors #62482

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Merged
mroeschke merged 7 commits into pandas-dev:main from Alvaro-Kothe:fix/mypy-errors
Sep 28, 2025
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3 changes: 1 addition & 2 deletions pandas/_typing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,8 +83,7 @@

# numpy compatible types
NumpyValueArrayLike: TypeAlias = ScalarLike_co | npt.ArrayLike
# Name "npt._ArrayLikeInt_co" is not defined [name-defined]
NumpySorter: TypeAlias = npt._ArrayLikeInt_co | None # type: ignore[name-defined]
NumpySorter: TypeAlias = npt._ArrayLikeInt_co | None


P = ParamSpec("P")
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17 changes: 9 additions & 8 deletions pandas/core/algorithms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -215,14 +215,15 @@ def _reconstruct_data(
# that values.dtype == dtype
cls = dtype.construct_array_type()

# error: Incompatible types in assignment (expression has type
# "ExtensionArray", variable has type "ndarray[Any, Any]")
values = cls._from_sequence(values, dtype=dtype) # type: ignore[assignment]

else:
values = values.astype(dtype, copy=False)

return values
# error: Incompatible return value type
# (got "ExtensionArray",
# expected "ndarray[tuple[Any, ...], dtype[Any]]")
return cls._from_sequence(values, dtype=dtype) # type: ignore[return-value]

# error: Incompatible return value type
# (got "ndarray[tuple[Any, ...], dtype[Any]]",
# expected "ExtensionArray")
return values.astype(dtype, copy=False) # type: ignore[return-value]


def _ensure_arraylike(values, func_name: str) -> ArrayLike:
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/array_algos/quantile.py
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Original file line number Diff line number Diff line change
Expand Up @@ -102,7 +102,7 @@ def quantile_with_mask(
interpolation=interpolation,
)

result = np.asarray(result) # type: ignore[assignment]
result = np.asarray(result)
result = result.T

return result
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4 changes: 3 additions & 1 deletion pandas/core/arrays/_mixins.py
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Original file line number Diff line number Diff line change
Expand Up @@ -151,7 +151,9 @@ def view(self, dtype: Dtype | None = None) -> ArrayLike:

td64_values = arr.view(dtype)
return TimedeltaArray._simple_new(td64_values, dtype=dtype)
return arr.view(dtype=dtype)
# error: Argument "dtype" to "view" of "ndarray" has incompatible type
# "ExtensionDtype | dtype[Any]"; expected "dtype[Any] | _HasDType[dtype[Any]]"
return arr.view(dtype=dtype) # type: ignore[arg-type]

def take(
self,
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/arrays/arrow/_arrow_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ def pyarrow_array_to_numpy_and_mask(
mask = pyarrow.BooleanArray.from_buffers(
pyarrow.bool_(), len(arr), [None, bitmask], offset=arr.offset
)
mask = np.asarray(mask) # type: ignore[assignment]
mask = np.asarray(mask)
else:
mask = np.ones(len(arr), dtype=bool)
return data, mask
4 changes: 2 additions & 2 deletions pandas/core/arrays/arrow/array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -657,7 +657,7 @@ def _box_pa_array(
):
arr_value = np.asarray(value, dtype=object)
# similar to isna(value) but exclude NaN, NaT, nat-like, nan-like
mask = is_pdna_or_none(arr_value) # type: ignore[assignment]
mask = is_pdna_or_none(arr_value)

try:
pa_array = pa.array(value, type=pa_type, mask=mask)
Expand Down Expand Up @@ -2738,7 +2738,7 @@ def _str_get_dummies(self, sep: str = "|", dtype: NpDtype | None = None):
dummies_dtype = np.bool_
dummies = np.zeros(n_rows * n_cols, dtype=dummies_dtype)
dummies[indices] = True
dummies = dummies.reshape((n_rows, n_cols)) # type: ignore[assignment]
dummies = dummies.reshape((n_rows, n_cols))
result = self._from_pyarrow_array(pa.array(list(dummies)))
return result, uniques_sorted.to_pylist()

Expand Down
2 changes: 1 addition & 1 deletion pandas/core/arrays/categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1869,7 +1869,7 @@ def value_counts(self, dropna: bool = True) -> Series:
count = np.bincount(obs, minlength=ncat or 0)
else:
count = np.bincount(np.where(mask, code, ncat))
ix = np.append(ix, -1) # type: ignore[assignment]
ix = np.append(ix, -1)

ix = coerce_indexer_dtype(ix, self.dtype.categories)
ix_categorical = self._from_backing_data(ix)
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6 changes: 5 additions & 1 deletion pandas/core/arrays/datetimes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -804,7 +804,11 @@ def _add_offset(self, offset: BaseOffset) -> Self:
try:
res_values = offset._apply_array(values._ndarray)
if res_values.dtype.kind == "i":
res_values = res_values.view(values.dtype)
# error: Argument 1 to "view" of "ndarray" has
# incompatible type
# "dtype[datetime64[date | int | None]] | DatetimeTZDtype";
# expected "dtype[Any] | _HasDType[dtype[Any]]" [arg-type]
res_values = res_values.view(values.dtype) # type: ignore[arg-type]
except NotImplementedError:
if get_option("performance_warnings"):
warnings.warn(
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/arrays/string_.py
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Original file line number Diff line number Diff line change
Expand Up @@ -764,7 +764,7 @@ def _cast_pointwise_result(self, values) -> ArrayLike:
result = super()._cast_pointwise_result(values)
if isinstance(result.dtype, StringDtype):
# Ensure we retain our same na_value/storage
result = result.astype(self.dtype) # type: ignore[call-overload]
result = result.astype(self.dtype)
return result

@classmethod
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/groupby/groupby.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1886,7 +1886,7 @@ def _apply_filter(self, indices, dropna):
mask.fill(False)
mask[indices.astype(int)] = True
# mask fails to broadcast when passed to where; broadcast manually.
mask = np.tile(mask, list(self._selected_obj.shape[1:]) + [1]).T # type: ignore[assignment]
mask = np.tile(mask, list(self._selected_obj.shape[1:]) + [1]).T
filtered = self._selected_obj.where(mask) # Fill with NaNs.
return filtered

Expand Down
8 changes: 4 additions & 4 deletions pandas/core/indexers/objects.py
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Original file line number Diff line number Diff line change
Expand Up @@ -131,8 +131,8 @@ def get_window_bounds(
if closed in ["left", "neither"]:
end -= 1

end = np.clip(end, 0, num_values) # type: ignore[assignment]
start = np.clip(start, 0, num_values) # type: ignore[assignment]
end = np.clip(end, 0, num_values)
start = np.clip(start, 0, num_values)

return start, end

Expand Down Expand Up @@ -402,7 +402,7 @@ def get_window_bounds(
start = np.arange(0, num_values, step, dtype="int64")
end = start + self.window_size
if self.window_size:
end = np.clip(end, 0, num_values) # type: ignore[assignment]
end = np.clip(end, 0, num_values)

return start, end

Expand Down Expand Up @@ -488,7 +488,7 @@ def get_window_bounds(
)
window_indices_start += len(indices)
# Extend as we'll be slicing window like [start, end)
window_indices = np.append(window_indices, [window_indices[-1] + 1]).astype( # type: ignore[assignment]
window_indices = np.append(window_indices, [window_indices[-1] + 1]).astype(
np.int64, copy=False
)
start_arrays.append(window_indices.take(ensure_platform_int(start)))
Expand Down
5 changes: 1 addition & 4 deletions pandas/core/methods/describe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -353,14 +353,11 @@ def _refine_percentiles(
if percentiles is None:
return np.array([0.25, 0.5, 0.75])

# explicit conversion of `percentiles` to list
percentiles = list(percentiles)
percentiles = np.asarray(percentiles)

# get them all to be in [0, 1]
validate_percentile(percentiles)

percentiles = np.asarray(percentiles)

# sort and check for duplicates
unique_pcts = np.unique(percentiles)
assert percentiles is not None
Expand Down
4 changes: 1 addition & 3 deletions pandas/core/nanops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -651,9 +651,7 @@ def _mask_datetimelike_result(
# we need to apply the mask
result = result.astype("i8").view(orig_values.dtype)
axis_mask = mask.any(axis=axis)
# error: Unsupported target for indexed assignment ("Union[ndarray[Any, Any],
# datetime64, timedelta64]")
result[axis_mask] = iNaT # type: ignore[index]
result[axis_mask] = iNaT
else:
if mask.any():
return np.int64(iNaT).view(orig_values.dtype)
Expand Down
2 changes: 1 addition & 1 deletion pandas/core/reshape/encoding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -359,7 +359,7 @@ def get_empty_frame(data) -> DataFrame:

if drop_first:
# remove first GH12042
dummy_mat = dummy_mat[:, 1:] # type: ignore[assignment]
dummy_mat = dummy_mat[:, 1:]
dummy_cols = dummy_cols[1:]
return DataFrame(dummy_mat, index=index, columns=dummy_cols, dtype=_dtype)

Expand Down
8 changes: 6 additions & 2 deletions pandas/core/reshape/merge.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1746,7 +1746,9 @@ def _maybe_coerce_merge_keys(self) -> None:

mask = ~np.isnan(lk)
match = lk == casted
if not match[mask].all():
# error: Item "ExtensionArray" of
# "ExtensionArray | Any" has no attribute "all"
if not match[mask].all(): # type: ignore[union-attr]
warnings.warn(
"You are merging on int and float "
"columns where the float values "
Expand All @@ -1766,7 +1768,9 @@ def _maybe_coerce_merge_keys(self) -> None:

mask = ~np.isnan(rk)
match = rk == casted
if not match[mask].all():
# error: Item "ExtensionArray" of
# "ExtensionArray | Any" has no attribute "all"
if not match[mask].all(): # type: ignore[union-attr]
warnings.warn(
"You are merging on int and float "
"columns where the float values "
Expand Down
4 changes: 2 additions & 2 deletions pandas/core/util/hashing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -324,8 +324,8 @@ def _hash_ndarray(
)

codes, categories = factorize(vals, sort=False)
dtype = CategoricalDtype(categories=Index(categories), ordered=False)
cat = Categorical._simple_new(codes, dtype)
tdtype = CategoricalDtype(categories=Index(categories), ordered=False)
cat = Categorical._simple_new(codes, tdtype)
return cat._hash_pandas_object(
encoding=encoding, hash_key=hash_key, categorize=False
)
Expand Down
13 changes: 5 additions & 8 deletions pandas/io/pytables.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3301,18 +3301,16 @@ def write_array(
# store as UTC
# with a zone

# error: Item "ExtensionArray" of "Union[Any, ExtensionArray]" has no
# attribute "asi8"
# error: "ExtensionArray" has no attribute "asi8"
self._handle.create_array(
self.group,
key,
value.asi8, # type: ignore[union-attr]
value.asi8, # type: ignore[attr-defined]
)

node = getattr(self.group, key)
# error: Item "ExtensionArray" of "Union[Any, ExtensionArray]" has no
# attribute "tz"
node._v_attrs.tz = _get_tz(value.tz) # type: ignore[union-attr]
# error: "ExtensionArray" has no attribute "tz"
node._v_attrs.tz = _get_tz(value.tz) # type: ignore[attr-defined]
node._v_attrs.value_type = f"datetime64[{value.dtype.unit}]"
elif lib.is_np_dtype(value.dtype, "m"):
self._handle.create_array(self.group, key, value.view("i8"))
Expand Down Expand Up @@ -5195,8 +5193,7 @@ def _maybe_convert_for_string_atom(
columns: list[str],
):
if isinstance(bvalues.dtype, StringDtype):
# "ndarray[Any, Any]" has no attribute "to_numpy"
bvalues = bvalues.to_numpy() # type: ignore[union-attr]
bvalues = bvalues.to_numpy()
if bvalues.dtype != object:
return bvalues

Expand Down
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