From 8700ee014a5832880b781c249b7094b882ac7631 Mon Sep 17 00:00:00 2001
From: Brock <jbrockmendel@gmail.com>
Date: Thu, 11 Mar 2021 19:29:28 -0800
Subject: [PATCH 1/6] TYP: fix ignores

---
 pandas/core/groupby/groupby.py      | 28 +++++++++-------------------
 pandas/core/groupby/ops.py          | 23 ++++++++---------------
 pandas/core/indexes/base.py         |  9 ++++++++-
 pandas/core/indexes/datetimelike.py |  7 ++++++-
 pandas/core/reshape/reshape.py      | 18 ++++++++++++------
 pandas/core/sorting.py              |  3 +--
 pandas/core/tools/datetimes.py      | 16 +++++-----------
 pandas/core/tools/numeric.py        |  7 +++----
 pandas/core/tools/timedeltas.py     |  6 ++----
 9 files changed, 54 insertions(+), 63 deletions(-)

diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index be8d641169b10..9de7e4c523625 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -68,7 +68,6 @@ class providing the base-class of operations.
     ensure_float,
     is_bool_dtype,
     is_datetime64_dtype,
-    is_extension_array_dtype,
     is_integer_dtype,
     is_numeric_dtype,
     is_object_dtype,
@@ -85,6 +84,7 @@ class providing the base-class of operations.
 from pandas.core.arrays import (
     Categorical,
     DatetimeArray,
+    ExtensionArray,
 )
 from pandas.core.base import (
     DataError,
@@ -2271,28 +2271,18 @@ def pre_processor(vals: np.ndarray) -> Tuple[np.ndarray, Optional[Type]]:
                     "'quantile' cannot be performed against 'object' dtypes!"
                 )
 
-            inference = None
+            inference: Optional[np.dtype] = None
             if is_integer_dtype(vals.dtype):
-                if is_extension_array_dtype(vals.dtype):
-                    # error: "ndarray" has no attribute "to_numpy"
-                    vals = vals.to_numpy(  # type: ignore[attr-defined]
-                        dtype=float, na_value=np.nan
-                    )
-                inference = np.int64
-            elif is_bool_dtype(vals.dtype) and is_extension_array_dtype(vals.dtype):
-                # error: "ndarray" has no attribute "to_numpy"
-                vals = vals.to_numpy(  # type: ignore[attr-defined]
-                    dtype=float, na_value=np.nan
-                )
+                if isinstance(vals, ExtensionArray):
+                    vals = vals.to_numpy(dtype=float, na_value=np.nan)
+                inference = np.dtype(np.int64)
+            elif is_bool_dtype(vals.dtype) and isinstance(vals, ExtensionArray):
+                vals = vals.to_numpy(dtype=float, na_value=np.nan)
             elif is_datetime64_dtype(vals.dtype):
-                # error: Incompatible types in assignment (expression has type
-                # "str", variable has type "Optional[Type[int64]]")
-                inference = "datetime64[ns]"  # type: ignore[assignment]
+                inference = np.dtype("datetime64[ns]")
                 vals = np.asarray(vals).astype(float)
             elif is_timedelta64_dtype(vals.dtype):
-                # error: Incompatible types in assignment (expression has type "str",
-                # variable has type "Optional[Type[signedinteger[Any]]]")
-                inference = "timedelta64[ns]"  # type: ignore[assignment]
+                inference = np.dtype("timedelta64[ns]")
                 vals = np.asarray(vals).astype(float)
 
             return vals, inference
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index 6495a4d26da3a..e505359987eb3 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -65,6 +65,7 @@
     is_timedelta64_dtype,
     needs_i8_conversion,
 )
+from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import ABCCategoricalIndex
 from pandas.core.dtypes.missing import (
     isna,
@@ -522,7 +523,7 @@ def _disallow_invalid_ops(self, values: ArrayLike, how: str):
     @final
     def _ea_wrap_cython_operation(
         self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs
-    ) -> Tuple[np.ndarray, Optional[List[str]]]:
+    ) -> np.ndarray:
         """
         If we have an ExtensionArray, unwrap, call _cython_operation, and
         re-wrap if appropriate.
@@ -539,10 +540,7 @@ def _ea_wrap_cython_operation(
             )
             if how in ["rank"]:
                 # preserve float64 dtype
-
-                # error: Incompatible return value type (got "ndarray", expected
-                # "Tuple[ndarray, Optional[List[str]]]")
-                return res_values  # type: ignore[return-value]
+                return res_values
 
             res_values = res_values.astype("i8", copy=False)
             result = type(orig_values)(res_values, dtype=orig_values.dtype)
@@ -555,14 +553,11 @@ def _ea_wrap_cython_operation(
                 kind, values, how, axis, min_count, **kwargs
             )
             dtype = maybe_cast_result_dtype(orig_values.dtype, how)
-            if is_extension_array_dtype(dtype):
-                # error: Item "dtype[Any]" of "Union[dtype[Any], ExtensionDtype]" has no
-                # attribute "construct_array_type"
-                cls = dtype.construct_array_type()  # type: ignore[union-attr]
+            if isinstance(dtype, ExtensionDtype):
+                cls = dtype.construct_array_type()
                 return cls._from_sequence(res_values, dtype=dtype)
-            # error: Incompatible return value type (got "ndarray", expected
-            # "Tuple[ndarray, Optional[List[str]]]")
-            return res_values  # type: ignore[return-value]
+
+            return res_values
 
         elif is_float_dtype(values.dtype):
             # FloatingArray
@@ -599,9 +594,7 @@ def _cython_operation(
         self._disallow_invalid_ops(values, how)
 
         if is_extension_array_dtype(values.dtype):
-            # error: Incompatible return value type (got "Tuple[ndarray,
-            # Optional[List[str]]]", expected "ndarray")
-            return self._ea_wrap_cython_operation(  # type: ignore[return-value]
+            return self._ea_wrap_cython_operation(
                 kind, values, how, axis, min_count, **kwargs
             )
 
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index b001139bef6c5..e17ca2078796f 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -3876,7 +3876,14 @@ def _reindex_non_unique(self, target):
     # --------------------------------------------------------------------
     # Join Methods
 
-    def join(self, other, how="left", level=None, return_indexers=False, sort=False):
+    def join(
+        self,
+        other,
+        how: str = "left",
+        level=None,
+        return_indexers: bool = False,
+        sort: bool = False,
+    ):
         """
         Compute join_index and indexers to conform data
         structures to the new index.
diff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py
index 96459970a9b57..0e32e5c5d2762 100644
--- a/pandas/core/indexes/datetimelike.py
+++ b/pandas/core/indexes/datetimelike.py
@@ -827,7 +827,12 @@ def _union(self, other, sort):
     _join_precedence = 10
 
     def join(
-        self, other, how: str = "left", level=None, return_indexers=False, sort=False
+        self,
+        other,
+        how: str = "left",
+        level=None,
+        return_indexers: bool = False,
+        sort: bool = False,
     ):
         """
         See Index.join
diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 13119b9997002..30889068030e2 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -2,6 +2,7 @@
 
 import itertools
 from typing import (
+    TYPE_CHECKING,
     List,
     Optional,
     Union,
@@ -44,6 +45,9 @@
     get_group_index_sorter,
 )
 
+if TYPE_CHECKING:
+    from pandas.core.arrays import ExtensionArray
+
 
 class _Unstacker:
     """
@@ -166,7 +170,7 @@ def _make_selectors(self):
 
         comp_index = ensure_platform_int(comp_index)
         stride = self.index.levshape[self.level] + self.lift
-        self.full_shape = ngroups, stride
+        self.full_shape = ngroups, int(stride)  # int() for mypy
 
         selector = self.sorted_labels[-1] + stride * comp_index + self.lift
         # error: Argument 1 to "zeros" has incompatible type "number"; expected
@@ -942,11 +946,11 @@ def _get_dummies_1d(
     data,
     prefix,
     prefix_sep="_",
-    dummy_na=False,
-    sparse=False,
-    drop_first=False,
+    dummy_na: bool = False,
+    sparse: bool = False,
+    drop_first: bool = False,
     dtype: Optional[Dtype] = None,
-):
+) -> DataFrame:
     from pandas.core.reshape.concat import concat
 
     # Series avoids inconsistent NaN handling
@@ -1045,7 +1049,9 @@ def get_empty_frame(data) -> DataFrame:
         return DataFrame(dummy_mat, index=index, columns=dummy_cols)
 
 
-def _reorder_for_extension_array_stack(arr, n_rows: int, n_columns: int):
+def _reorder_for_extension_array_stack(
+    arr: ExtensionArray, n_rows: int, n_columns: int
+) -> ExtensionArray:
     """
     Re-orders the values when stacking multiple extension-arrays.
 
diff --git a/pandas/core/sorting.py b/pandas/core/sorting.py
index ba81866602361..720643d3d98aa 100644
--- a/pandas/core/sorting.py
+++ b/pandas/core/sorting.py
@@ -43,7 +43,6 @@
 _INT64_MAX = np.iinfo(np.int64).max
 
 
-# error: Function "numpy.array" is not valid as a type
 def get_indexer_indexer(
     target: Index,
     level: Union[str, int, List[str], List[int]],
@@ -52,7 +51,7 @@ def get_indexer_indexer(
     na_position: str,
     sort_remaining: bool,
     key: IndexKeyFunc,
-) -> Optional[np.array]:  # type: ignore[valid-type]
+) -> Optional[np.ndarray]:
     """
     Helper method that return the indexer according to input parameters for
     the sort_index method of DataFrame and Series.
diff --git a/pandas/core/tools/datetimes.py b/pandas/core/tools/datetimes.py
index 1e71069e5be4d..2efce5db2a4a3 100644
--- a/pandas/core/tools/datetimes.py
+++ b/pandas/core/tools/datetimes.py
@@ -534,25 +534,19 @@ def _to_datetime_with_unit(arg, unit, name, tz, errors: Optional[str]) -> Index:
     # GH#30050 pass an ndarray to tslib.array_with_unit_to_datetime
     # because it expects an ndarray argument
     if isinstance(arg, IntegerArray):
-        result = arg.astype(f"datetime64[{unit}]")
+        res = arg.astype(f"datetime64[{unit}]")
         tz_parsed = None
     else:
-        result, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
+        res, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
 
     if errors == "ignore":
         # Index constructor _may_ infer to DatetimeIndex
-
-        # error: Incompatible types in assignment (expression has type "Index", variable
-        # has type "ExtensionArray")
-        result = Index(result, name=name)  # type: ignore[assignment]
+        result = Index(res, name=name)
     else:
-        # error: Incompatible types in assignment (expression has type "DatetimeIndex",
-        # variable has type "ExtensionArray")
-        result = DatetimeIndex(result, name=name)  # type: ignore[assignment]
+        result = DatetimeIndex(res, name=name)
 
     if not isinstance(result, DatetimeIndex):
-        # error: Incompatible return value type (got "ExtensionArray", expected "Index")
-        return result  # type: ignore[return-value]
+        return result
 
     # GH#23758: We may still need to localize the result with tz
     # GH#25546: Apply tz_parsed first (from arg), then tz (from caller)
diff --git a/pandas/core/tools/numeric.py b/pandas/core/tools/numeric.py
index 31ab78e59a556..b7116ee95949b 100644
--- a/pandas/core/tools/numeric.py
+++ b/pandas/core/tools/numeric.py
@@ -1,3 +1,5 @@
+from typing import Optional
+
 import numpy as np
 
 from pandas._libs import lib
@@ -164,13 +166,10 @@ def to_numeric(arg, errors="raise", downcast=None):
 
     # GH33013: for IntegerArray & FloatingArray extract non-null values for casting
     # save mask to reconstruct the full array after casting
+    mask: Optional[np.ndarray] = None
     if isinstance(values, NumericArray):
         mask = values._mask
         values = values._data[~mask]
-    else:
-        # error: Incompatible types in assignment (expression has type "None", variable
-        # has type "ndarray")
-        mask = None  # type: ignore[assignment]
 
     values_dtype = getattr(values, "dtype", None)
     if is_numeric_dtype(values_dtype):
diff --git a/pandas/core/tools/timedeltas.py b/pandas/core/tools/timedeltas.py
index a8378e91f9375..047cec6501627 100644
--- a/pandas/core/tools/timedeltas.py
+++ b/pandas/core/tools/timedeltas.py
@@ -165,7 +165,7 @@ def _convert_listlike(arg, unit=None, errors="raise", name=None):
         arg = np.array(list(arg), dtype=object)
 
     try:
-        value = sequence_to_td64ns(arg, unit=unit, errors=errors, copy=False)[0]
+        td64arr = sequence_to_td64ns(arg, unit=unit, errors=errors, copy=False)[0]
     except ValueError:
         if errors == "ignore":
             return arg
@@ -181,7 +181,5 @@ def _convert_listlike(arg, unit=None, errors="raise", name=None):
 
     from pandas import TimedeltaIndex
 
-    # error: Incompatible types in assignment (expression has type "TimedeltaIndex",
-    # variable has type "ndarray")
-    value = TimedeltaIndex(value, unit="ns", name=name)  # type: ignore[assignment]
+    value = TimedeltaIndex(td64arr, unit="ns", name=name)
     return value

From 4cca1bb60d247048e090abbc4cc3a2735d7b3618 Mon Sep 17 00:00:00 2001
From: Simon Hawkins <simonjayhawkins@gmail.com>
Date: Fri, 12 Mar 2021 11:01:17 +0000
Subject: [PATCH 2/6] mypy fixup

---
 pandas/core/groupby/groupby.py | 2 +-
 pandas/core/indexes/base.py    | 2 +-
 pandas/core/reshape/reshape.py | 3 +++
 3 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 9de7e4c523625..c56f865796798 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -2265,7 +2265,7 @@ def quantile(self, q=0.5, interpolation: str = "linear"):
         """
         from pandas import concat
 
-        def pre_processor(vals: np.ndarray) -> Tuple[np.ndarray, Optional[Type]]:
+        def pre_processor(vals: np.ndarray) -> Tuple[np.ndarray, Optional[np.dtype]]:
             if is_object_dtype(vals):
                 raise TypeError(
                     "'quantile' cannot be performed against 'object' dtypes!"
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index e17ca2078796f..8b67b98b32f7f 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -3879,7 +3879,7 @@ def _reindex_non_unique(self, target):
     def join(
         self,
         other,
-        how: str = "left",
+        how: str_t = "left",
         level=None,
         return_indexers: bool = False,
         sort: bool = False,
diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 30889068030e2..21e0ebc338de9 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -6,6 +6,7 @@
     List,
     Optional,
     Union,
+    cast,
 )
 
 import numpy as np
@@ -1033,6 +1034,8 @@ def get_empty_frame(data) -> DataFrame:
             sparse_series.append(Series(data=sarr, index=index, name=col))
 
         out = concat(sparse_series, axis=1, copy=False)
+        # TODO: overload concat with Literal for axis
+        out = cast(DataFrame, out)
         return out
 
     else:

From 6cfc1ea715b6377feed7ae70908c61ab367d9f6b Mon Sep 17 00:00:00 2001
From: Brock <jbrockmendel@gmail.com>
Date: Fri, 12 Mar 2021 07:10:09 -0800
Subject: [PATCH 3/6] update annotations

---
 pandas/core/groupby/groupby.py | 3 ++-
 pandas/core/reshape/reshape.py | 2 +-
 pandas/core/tools/datetimes.py | 8 ++++----
 3 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 9de7e4c523625..d749e82178e34 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -46,6 +46,7 @@ class providing the base-class of operations.
 )
 import pandas._libs.groupby as libgroupby
 from pandas._typing import (
+    ArrayLike,
     F,
     FrameOrSeries,
     FrameOrSeriesUnion,
@@ -2265,7 +2266,7 @@ def quantile(self, q=0.5, interpolation: str = "linear"):
         """
         from pandas import concat
 
-        def pre_processor(vals: np.ndarray) -> Tuple[np.ndarray, Optional[Type]]:
+        def pre_processor(vals: ArrayLike) -> Tuple[np.ndarray, Optional[np.dtype]]:
             if is_object_dtype(vals):
                 raise TypeError(
                     "'quantile' cannot be performed against 'object' dtypes!"
diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 30889068030e2..e0f09614c4597 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -170,7 +170,7 @@ def _make_selectors(self):
 
         comp_index = ensure_platform_int(comp_index)
         stride = self.index.levshape[self.level] + self.lift
-        self.full_shape = ngroups, int(stride)  # int() for mypy
+        self.full_shape = ngroups, stride
 
         selector = self.sorted_labels[-1] + stride * comp_index + self.lift
         # error: Argument 1 to "zeros" has incompatible type "number"; expected
diff --git a/pandas/core/tools/datetimes.py b/pandas/core/tools/datetimes.py
index 2efce5db2a4a3..9822356d11d7c 100644
--- a/pandas/core/tools/datetimes.py
+++ b/pandas/core/tools/datetimes.py
@@ -534,16 +534,16 @@ def _to_datetime_with_unit(arg, unit, name, tz, errors: Optional[str]) -> Index:
     # GH#30050 pass an ndarray to tslib.array_with_unit_to_datetime
     # because it expects an ndarray argument
     if isinstance(arg, IntegerArray):
-        res = arg.astype(f"datetime64[{unit}]")
+        arr = arg.astype(f"datetime64[{unit}]")
         tz_parsed = None
     else:
-        res, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
+        arr, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
 
     if errors == "ignore":
         # Index constructor _may_ infer to DatetimeIndex
-        result = Index(res, name=name)
+        result = Index(arr, name=name)
     else:
-        result = DatetimeIndex(res, name=name)
+        result = DatetimeIndex(arr, name=name)
 
     if not isinstance(result, DatetimeIndex):
         return result

From f03029b0c9708196cb336c8ec714c6ee252d9849 Mon Sep 17 00:00:00 2001
From: Brock <jbrockmendel@gmail.com>
Date: Fri, 12 Mar 2021 08:03:38 -0800
Subject: [PATCH 4/6] mypy fixup

---
 pandas/core/groupby/groupby.py | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index d749e82178e34..ac398ef2f11a9 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -2275,18 +2275,22 @@ def pre_processor(vals: ArrayLike) -> Tuple[np.ndarray, Optional[np.dtype]]:
             inference: Optional[np.dtype] = None
             if is_integer_dtype(vals.dtype):
                 if isinstance(vals, ExtensionArray):
-                    vals = vals.to_numpy(dtype=float, na_value=np.nan)
+                    out = vals.to_numpy(dtype=float, na_value=np.nan)
+                else:
+                    out = vals
                 inference = np.dtype(np.int64)
             elif is_bool_dtype(vals.dtype) and isinstance(vals, ExtensionArray):
-                vals = vals.to_numpy(dtype=float, na_value=np.nan)
+                out = vals.to_numpy(dtype=float, na_value=np.nan)
             elif is_datetime64_dtype(vals.dtype):
                 inference = np.dtype("datetime64[ns]")
-                vals = np.asarray(vals).astype(float)
+                out = np.asarray(vals).astype(float)
             elif is_timedelta64_dtype(vals.dtype):
                 inference = np.dtype("timedelta64[ns]")
-                vals = np.asarray(vals).astype(float)
+                out = np.asarray(vals).astype(float)
+            else:
+                out = np.asarray(out)
 
-            return vals, inference
+            return out, inference
 
         def post_processor(vals: np.ndarray, inference: Optional[Type]) -> np.ndarray:
             if inference:

From 926936b15ab4127a4cfd094272d14c297453603d Mon Sep 17 00:00:00 2001
From: Brock <jbrockmendel@gmail.com>
Date: Fri, 12 Mar 2021 08:57:32 -0800
Subject: [PATCH 5/6] typo fixup

---
 pandas/core/groupby/groupby.py | 2 +-
 pandas/core/resample.py        | 6 +++++-
 2 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index ac398ef2f11a9..979c7aa990184 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -2288,7 +2288,7 @@ def pre_processor(vals: ArrayLike) -> Tuple[np.ndarray, Optional[np.dtype]]:
                 inference = np.dtype("timedelta64[ns]")
                 out = np.asarray(vals).astype(float)
             else:
-                out = np.asarray(out)
+                out = np.asarray(vals)
 
             return out, inference
 
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 2308f9edb4328..342c05038304d 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -24,6 +24,7 @@
     to_offset,
 )
 from pandas._typing import (
+    FrameOrSeries,
     T,
     TimedeltaConvertibleTypes,
     TimestampConvertibleTypes,
@@ -1742,7 +1743,10 @@ def _get_period_bins(self, ax: PeriodIndex):
         return binner, bins, labels
 
 
-def _take_new_index(obj, indexer, new_index, axis=0):
+# TODO: type indexer as ndarray[np.intp] once dtypes can be annotated
+def _take_new_index(
+    obj: FrameOrSeries, indexer: np.ndarray, new_index, axis: int = 0
+) -> FrameOrSeries:
 
     if isinstance(obj, ABCSeries):
         new_values = algos.take_nd(obj._values, indexer)

From f559025a8f1ddaa82707b78402dae955da101888 Mon Sep 17 00:00:00 2001
From: Brock <jbrockmendel@gmail.com>
Date: Fri, 12 Mar 2021 09:56:51 -0800
Subject: [PATCH 6/6] revert accidental commit

---
 pandas/core/resample.py | 6 +-----
 1 file changed, 1 insertion(+), 5 deletions(-)

diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 342c05038304d..2308f9edb4328 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -24,7 +24,6 @@
     to_offset,
 )
 from pandas._typing import (
-    FrameOrSeries,
     T,
     TimedeltaConvertibleTypes,
     TimestampConvertibleTypes,
@@ -1743,10 +1742,7 @@ def _get_period_bins(self, ax: PeriodIndex):
         return binner, bins, labels
 
 
-# TODO: type indexer as ndarray[np.intp] once dtypes can be annotated
-def _take_new_index(
-    obj: FrameOrSeries, indexer: np.ndarray, new_index, axis: int = 0
-) -> FrameOrSeries:
+def _take_new_index(obj, indexer, new_index, axis=0):
 
     if isinstance(obj, ABCSeries):
         new_values = algos.take_nd(obj._values, indexer)