TYP: remove some ignores (#42368)

Author: simonjayhawkins

pandas/_testing/asserters.py

@@ -107,6 +107,7 @@ def assert_almost_equal(
             FutureWarning,
             stacklevel=2,
         )
+        # https://github.com/python/mypy/issues/7642
         # error: Argument 1 to "_get_tol_from_less_precise" has incompatible
         # type "Union[bool, int, NoDefault]"; expected "Union[bool, int]"
         rtol = atol = _get_tol_from_less_precise(
@@ -340,6 +341,7 @@ def _get_ilevel_values(index, level):
             FutureWarning,
             stacklevel=2,
         )
+        # https://github.com/python/mypy/issues/7642
         # error: Argument 1 to "_get_tol_from_less_precise" has incompatible
         # type "Union[bool, int, NoDefault]"; expected "Union[bool, int]"
         rtol = atol = _get_tol_from_less_precise(

pandas/core/algorithms.py

@@ -1187,13 +1187,10 @@ def _get_score(at):
 
     if is_scalar(q):
         return _get_score(q)
-    else:
-        q = np.asarray(q, np.float64)
-        result = [_get_score(x) for x in q]
-        # error: Incompatible types in assignment (expression has type
-        # "ndarray", variable has type "List[Any]")
-        result = np.array(result, dtype=np.float64)  # type: ignore[assignment]
-        return result
+
+    q = np.asarray(q, np.float64)
+    result = [_get_score(x) for x in q]
+    return np.array(result, dtype=np.float64)
 
 
 # --------------- #

pandas/core/apply.py

@@ -7,6 +7,7 @@
     Any,
     Dict,
     Hashable,
+    Iterable,
     Iterator,
     List,
     cast,
@@ -443,16 +444,15 @@ def agg_dict_like(self) -> DataFrame | Series:
 
         # combine results
         if all(is_ndframe):
+            keys_to_use: Iterable[Hashable]
             keys_to_use = [k for k in keys if not results[k].empty]
             # Have to check, if at least one DataFrame is not empty.
             keys_to_use = keys_to_use if keys_to_use != [] else keys
             if selected_obj.ndim == 2:
                 # keys are columns, so we can preserve names
                 ktu = Index(keys_to_use)
                 ktu._set_names(selected_obj.columns.names)
-                # Incompatible types in assignment (expression has type "Index",
-                # variable has type "List[Hashable]")
-                keys_to_use = ktu  # type: ignore[assignment]
+                keys_to_use = ktu
 
             axis = 0 if isinstance(obj, ABCSeries) else 1
             result = concat(

pandas/core/base.py

@@ -19,12 +19,12 @@
 import pandas._libs.lib as lib
 from pandas._typing import (
     ArrayLike,
-    Dtype,
     DtypeObj,
     FrameOrSeries,
     IndexLabel,
     Shape,
     final,
+    npt,
 )
 from pandas.compat import PYPY
 from pandas.compat.numpy import function as nv
@@ -411,7 +411,7 @@ def array(self) -> ExtensionArray:
 
     def to_numpy(
         self,
-        dtype: Dtype | None = None,
+        dtype: npt.DTypeLike | None = None,
         copy: bool = False,
         na_value=lib.no_default,
         **kwargs,
@@ -510,21 +510,24 @@ def to_numpy(
         """
         if is_extension_array_dtype(self.dtype):
             # error: Too many arguments for "to_numpy" of "ExtensionArray"
+
+            # error: Argument 1 to "to_numpy" of "ExtensionArray" has incompatible type
+            # "Optional[Union[dtype[Any], None, type, _SupportsDType[dtype[Any]], str,
+            # Union[Tuple[Any, int], Tuple[Any, Union[SupportsIndex,
+            # Sequence[SupportsIndex]]], List[Any], _DTypeDict, Tuple[Any, Any]]]]";
+            # expected "Optional[Union[ExtensionDtype, Union[str, dtype[Any]],
+            # Type[str], Type[float], Type[int], Type[complex], Type[bool],
+            # Type[object]]]"
             return self.array.to_numpy(  # type: ignore[call-arg]
-                dtype, copy=copy, na_value=na_value, **kwargs
+                dtype, copy=copy, na_value=na_value, **kwargs  # type: ignore[arg-type]
             )
         elif kwargs:
             bad_keys = list(kwargs.keys())[0]
             raise TypeError(
                 f"to_numpy() got an unexpected keyword argument '{bad_keys}'"
             )
 
-        # error: Argument "dtype" to "asarray" has incompatible type
-        # "Union[ExtensionDtype, str, dtype[Any], Type[str], Type[float], Type[int],
-        # Type[complex], Type[bool], Type[object], None]"; expected "Union[dtype[Any],
-        # None, type, _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any, Union[int,
-        # Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
-        result = np.asarray(self._values, dtype=dtype)  # type: ignore[arg-type]
+        result = np.asarray(self._values, dtype=dtype)
         # TODO(GH-24345): Avoid potential double copy
         if copy or na_value is not lib.no_default:
             result = result.copy()
@@ -1091,6 +1094,7 @@ def _memory_usage(self, deep: bool = False) -> int:
         are not components of the array if deep=False or if used on PyPy
         """
         if hasattr(self.array, "memory_usage"):
+            # https://github.com/python/mypy/issues/1424
             # error: "ExtensionArray" has no attribute "memory_usage"
             return self.array.memory_usage(deep=deep)  # type: ignore[attr-defined]
 

pandas/core/frame.py

@@ -7614,6 +7614,7 @@ def groupby(
             raise TypeError("You have to supply one of 'by' and 'level'")
         axis = self._get_axis_number(axis)
 
+        # https://github.com/python/mypy/issues/7642
         # error: Argument "squeeze" to "DataFrameGroupBy" has incompatible type
         # "Union[bool, NoDefault]"; expected "bool"
         return DataFrameGroupBy(