diff --git a/pyproject.toml b/pyproject.toml
index 291fd063aeb..5f5901d522f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -2,6 +2,9 @@
 
 [tool.mypy]
 ignore_missing_imports = true
+ignore_errors = false
+enable_error_code = "ignore-without-code"
+warn_unused_ignores = true
 # If we don't specify this, then mypy will check excluded files if
 # they are imported by a checked file.
 follow_imports = "skip"
diff --git a/python/cudf/cudf/core/accessors/string.py b/python/cudf/cudf/core/accessors/string.py
index e67eb6161d2..fa0932b93d9 100644
--- a/python/cudf/cudf/core/accessors/string.py
+++ b/python/cudf/cudf/core/accessors/string.py
@@ -503,7 +503,7 @@ def join(
         else:
             # If self._column is not a ListColumn, we will have to
             # split each row by character and create a ListColumn out of it.
-            list_column = self._column.fillna("").character_tokenize()  # type: ignore[assignment]
+            list_column = self._column.fillna("").character_tokenize()
             if len(list_column) == 0:
                 list_column = column_empty(  # type: ignore[assignment]
                     len(self._column), dtype=list_column.dtype
@@ -524,9 +524,9 @@ def join(
                     f"of type: {type(sep_na_rep)}"
                 )
             data = list_column.join_list_elements(  # type: ignore[attr-defined]
-                sep_column,  # type: ignore[arg-type]
+                sep_column,
                 sep_na_rep,
-                string_na_rep,  # type: ignore[arg-type]
+                string_na_rep,
             )
         else:
             raise TypeError(
@@ -753,7 +753,7 @@ def contains(
                 result_col = self._column.contains_re(pat, flags)  # type: ignore[arg-type]
             else:
                 if case is False:
-                    input_column = self._column.to_lower()  # type: ignore[union-attr]
+                    input_column = self._column.to_lower()
                     pat_normed = pat.lower()  # type: ignore[union-attr]
                 else:
                     input_column = self._column
@@ -763,7 +763,7 @@ def contains(
             # TODO: we silently ignore the `regex=` flag here
             col_pat = as_column(pat, dtype=CUDF_STRING_DTYPE)
             if case is False:
-                input_column = self._column.to_lower()  # type: ignore[union-attr]
+                input_column = self._column.to_lower()
                 col_pat = col_pat.to_lower()  # type: ignore[attr-defined]
             else:
                 input_column = self._column
@@ -990,7 +990,7 @@ def replace(
 
         # Pandas forces non-regex replace when pat is a single-character
         if regex is True and len(pat) > 1:
-            result = self._column.replace_re(  # type: ignore[arg-type]
+            result = self._column.replace_re(
                 pat,  # type: ignore[arg-type]
                 pa_repl,
                 n,
@@ -1106,7 +1106,7 @@ def slice(
         dtype: object
         """
         return self._return_or_inplace(
-            self._column.slice_strings(start, stop, step)  # type: ignore[arg-type]
+            self._column.slice_strings(start, stop, step)
         )
 
     def isinteger(self) -> Series | Index:
@@ -2133,7 +2133,7 @@ def slice_from(self, starts: Series, stops: Series) -> Series | Index:
         dtype: object
         """
         return self._return_or_inplace(
-            self._column.slice_strings(starts._column, stops._column)  # type: ignore[arg-type]
+            self._column.slice_strings(starts._column, stops._column)
         )
 
     def slice_replace(
@@ -2320,13 +2320,13 @@ def get(self, i: int = 0) -> Series | Index:
         if i < 0:
             next_index = i - 1
             step = -1
-            to_mask = str_lens < abs(i)  # type: ignore[operator]
+            to_mask = str_lens < abs(i)
         else:
             next_index = i + 1
             step = 1
-            to_mask = str_lens <= i  # type: ignore[operator]
+            to_mask = str_lens <= i
         result = self.slice(i, next_index, step)
-        if to_mask.any():  # type: ignore[union-attr]
+        if to_mask.any():
             result[to_mask] = pd.NA  # type: ignore[index]
         return result
 
@@ -3796,7 +3796,7 @@ def _starts_ends_with(
         pat: str | tuple[str, ...],
     ) -> Series | Index:
         return self._return_or_inplace(
-            self._column.starts_ends_with(method, pat)  # type: ignore[arg-type]
+            self._column.starts_ends_with(method, pat)
         )
 
     def endswith(self, pat: str | tuple[str, ...]) -> Series | Index:
@@ -3917,10 +3917,10 @@ def removesuffix(self, suffix: str) -> Series | Index:
         """
         if suffix is None or len(suffix) == 0:
             return self._return_or_inplace(self._column)
-        ends_column = self.endswith(suffix)._column  # type: ignore[union-attr]
-        removed_column = self.slice(0, -len(suffix), None)._column  # type: ignore[union-attr]
+        ends_column = self.endswith(suffix)._column
+        removed_column = self.slice(0, -len(suffix), None)._column
 
-        result = removed_column.copy_if_else(self._column, ends_column)  # type: ignore[arg-type]
+        result = removed_column.copy_if_else(self._column, ends_column)
         return self._return_or_inplace(result)
 
     def removeprefix(self, prefix: str) -> Series | Index:
@@ -3956,9 +3956,9 @@ def removeprefix(self, prefix: str) -> Series | Index:
         """
         if prefix is None or len(prefix) == 0:
             return self._return_or_inplace(self._column)
-        starts_column = self.startswith(prefix)._column  # type: ignore[union-attr]
-        removed_column = self.slice(len(prefix), None, None)._column  # type: ignore[union-attr]
-        result = removed_column.copy_if_else(self._column, starts_column)  # type: ignore[arg-type]
+        starts_column = self.startswith(prefix)._column
+        removed_column = self.slice(len(prefix), None, None)._column
+        result = removed_column.copy_if_else(self._column, starts_column)
         return self._return_or_inplace(result)
 
     def _find(
@@ -4125,7 +4125,7 @@ def index(
         if end is None:
             end = -1
 
-        result_col = self.find(sub, start, end)._column  # type: ignore[union-attr]
+        result_col = self.find(sub, start, end)._column
 
         result = self._return_or_inplace(result_col)
 
@@ -4187,7 +4187,7 @@ def rindex(
         if end is None:
             end = -1
 
-        result_col = self.rfind(sub, start, end)._column  # type: ignore[union-attr]
+        result_col = self.rfind(sub, start, end)._column
 
         result = self._return_or_inplace(result_col)
 
@@ -4494,7 +4494,7 @@ def tokenize(self, delimiter: str = " ") -> Series | Index:
 
         if isinstance(delim, ColumnBase):
             result = self._return_or_inplace(
-                self._column.tokenize_column(delim),  # type: ignore[arg-type]
+                self._column.tokenize_column(delim),
                 retain_index=False,
             )
         elif isinstance(delim, plc.Scalar):
@@ -4508,7 +4508,7 @@ def tokenize(self, delimiter: str = " ") -> Series | Index:
                 for delimiters, but got {type(delimiter)}"
             )
         if isinstance(self._parent, cudf.Series):
-            result.index = self._parent.index.repeat(  # type: ignore
+            result.index = self._parent.index.repeat(  # type: ignore[union-attr]
                 self.token_count(delimiter=delimiter)
             )
         return result
@@ -4635,12 +4635,12 @@ def token_count(self, delimiter: str = " ") -> Series | Index:
         delim = _massage_string_arg(delimiter, "delimiter", allow_col=True)
         if isinstance(delim, ColumnBase):
             return self._return_or_inplace(
-                self._column.count_tokens_column(delim)  # type: ignore[arg-type]
+                self._column.count_tokens_column(delim)
             )
 
         elif isinstance(delim, plc.Scalar):
             return self._return_or_inplace(
-                self._column.count_tokens_scalar(delim)  # type: ignore[arg-type]
+                self._column.count_tokens_scalar(delim)
             )
         else:
             raise TypeError(
@@ -4734,7 +4734,7 @@ def character_ngrams(
         if isinstance(result, cudf.Series) and not as_list:
             # before exploding, removes those lists which have 0 length
             result = result[result.list.len() > 0]
-            return result.explode()  # type: ignore
+            return result.explode()  # type: ignore[union-attr]
         return result
 
     def hash_character_ngrams(
@@ -5032,9 +5032,7 @@ def is_consonant(self, position) -> Series | Index:
         """
         if can_convert_to_column(position):
             position = as_column(position)
-        return self._return_or_inplace(
-            self._column.is_letter(False, position)  # type: ignore[arg-type]
-        )
+        return self._return_or_inplace(self._column.is_letter(False, position))
 
     def is_vowel(self, position) -> Series | Index:
         """
@@ -5069,9 +5067,7 @@ def is_vowel(self, position) -> Series | Index:
         """
         if can_convert_to_column(position):
             position = as_column(position)
-        return self._return_or_inplace(
-            self._column.is_letter(True, position)  # type: ignore[arg-type]
-        )
+        return self._return_or_inplace(self._column.is_letter(True, position))
 
     def build_suffix_array(self, min_width: int) -> Series | Index:
         """
@@ -5095,7 +5091,7 @@ def build_suffix_array(self, min_width: int) -> Series | Index:
             New column of suffix array
         """
         return self._return_or_inplace(
-            self._column.build_suffix_array(min_width),  # type: ignore[arg-type]
+            self._column.build_suffix_array(min_width),
             inplace=False,
             expand=False,
             retain_index=False,
@@ -5124,7 +5120,7 @@ def resolve_duplicates(self, sa, min_width: int) -> Series | Index:
         """
         sa_column = sa._column
         return self._return_or_inplace(
-            self._column.resolve_duplicates(sa_column, min_width),  # type: ignore[arg-type]
+            self._column.resolve_duplicates(sa_column, min_width),
             inplace=False,
             expand=False,
             retain_index=False,
@@ -5163,7 +5159,7 @@ def resolve_duplicates_pair(
         return self._return_or_inplace(
             self._column.resolve_duplicates_pair(
                 sa1_col, input2_col, sa2_col, min_width
-            ),  # type: ignore[arg-type]
+            ),
             inplace=False,
             expand=False,
             retain_index=False,
@@ -5505,5 +5501,5 @@ def jaccard_index(self, input: Series, width: int) -> Series | Index:
         dtype: float32
         """
         return self._return_or_inplace(
-            self._column.jaccard_index(input._column, width)  # type: ignore[arg-type]
+            self._column.jaccard_index(input._column, width)
         )
diff --git a/python/cudf/cudf/core/column/categorical.py b/python/cudf/cudf/core/column/categorical.py
index 512dbdda59e..a5f1bdf999f 100644
--- a/python/cudf/cudf/core/column/categorical.py
+++ b/python/cudf/cudf/core/column/categorical.py
@@ -81,7 +81,7 @@ class CategoricalColumn(column.ColumnBase):
     """
 
     dtype: CategoricalDtype
-    _children: tuple[NumericalColumn]  # type: ignore[assignment]
+    _children: tuple[NumericalColumn]
     _VALID_REDUCTIONS = {
         "max",
         "min",
@@ -103,7 +103,7 @@ def __init__(
         mask: Buffer | None,
         offset: int,
         null_count: int,
-        children: tuple[NumericalColumn],  # type: ignore[assignment]
+        children: tuple[NumericalColumn],
     ):
         if data is not None:
             raise ValueError(f"{data=} must be None")
@@ -438,7 +438,7 @@ def find_and_replace(
             # However, it seems that this functionality has been broken for a
             # long time so for now we're just having mypy ignore and we'll come
             # back to this.
-            if fill_value in self.categories:  # type: ignore
+            if fill_value in self.categories:  # type: ignore[operator]
                 replaced = self.fillna(fill_value)
             else:
                 new_categories = self.categories.append(
@@ -703,7 +703,7 @@ def _concat(
         elif newsize == 0:
             codes_col = column.column_empty(0, head.codes.dtype)
         else:
-            codes_col = column.concat_columns(codes)  # type: ignore[arg-type]
+            codes_col = column.concat_columns(codes)
 
         return codes_col._with_type_metadata(CategoricalDtype(categories=cats))  # type: ignore[return-value]
 
diff --git a/python/cudf/cudf/core/column/column.py b/python/cudf/cudf/core/column/column.py
index 86766b48d31..db0aece973a 100644
--- a/python/cudf/cudf/core/column/column.py
+++ b/python/cudf/cudf/core/column/column.py
@@ -237,13 +237,13 @@ def size(self) -> int:
 
     @property
     def base_data(self) -> None | Buffer:
-        return self._base_data  # type: ignore[has-type]
+        return self._base_data
 
     @property
     def data(self) -> None | Buffer:
         if self.base_data is None:
             return None
-        if self._data is None:  # type: ignore[has-type]
+        if self._data is None:
             start = self.offset * self.dtype.itemsize
             end = start + self.size * self.dtype.itemsize
             self._data = self.base_data[start:end]  # type: ignore[assignment]
@@ -276,7 +276,7 @@ def set_base_data(self, value: None | Buffer) -> None:
                 f"got {type(value).__name__}"
             )
 
-        self._data = None  # type: ignore[assignment]
+        self._data = None
         self._base_data = value
 
     @property
@@ -288,11 +288,11 @@ def has_nulls(self, include_nan: bool = False) -> bool:
 
     @property
     def base_mask(self) -> None | Buffer:
-        return self._base_mask  # type: ignore[has-type]
+        return self._base_mask
 
     @property
     def mask(self) -> None | Buffer:
-        if self._mask is None:  # type: ignore[has-type]
+        if self._mask is None:
             if self.base_mask is None or self.offset == 0:
                 self._mask = self.base_mask  # type: ignore[assignment]
             else:
@@ -412,7 +412,7 @@ def null_count(self) -> int:
             else:
                 with acquire_spill_lock():
                     self._null_count = plc.null_mask.null_count(
-                        plc.gpumemoryview(self.base_mask),  # type: ignore[union-attr]
+                        plc.gpumemoryview(self.base_mask),
                         self.offset,
                         self.offset + self.size,
                     )
@@ -424,7 +424,7 @@ def offset(self) -> int:
 
     @property
     def base_children(self) -> tuple[ColumnBase, ...]:
-        return self._base_children  # type: ignore[has-type]
+        return self._base_children
 
     @property
     def children(self) -> tuple[ColumnBase, ...]:
@@ -686,7 +686,7 @@ def from_cuda_array_interface(cls, arbitrary: Any) -> ColumnBase:
                     f"expected {required_num_bytes} bytes."
                 )
             column = column.set_mask(mask_buff)
-        return column  # type: ignore[return-value]
+        return column
 
     def __len__(self) -> int:
         return self.size
@@ -784,7 +784,7 @@ def clip(self, lo: ScalarLike, hi: ScalarLike) -> Self:
                 pa.scalar(hi, type=cudf_dtype_to_pa_type(self.dtype))
             ),
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     def equals(self, other: ColumnBase, check_dtypes: bool = False) -> bool:
         if not isinstance(other, ColumnBase) or len(self) != len(other):
@@ -987,7 +987,7 @@ def _fill(
                 )
             if self.dtype == CUDF_STRING_DTYPE:
                 return self._mimic_inplace(result, inplace=True)
-            return result  # type: ignore[return-value]
+            return result
 
         if not fill_value.is_valid() and not self.nullable:
             mask = as_buffer(
@@ -1014,7 +1014,7 @@ def shift(self, offset: int, fill_value: ScalarLike) -> Self:
             offset,
             plc_fill_value,
         )
-        return type(self).from_pylibcudf(plc_col)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_col)
 
     def copy(self, deep: bool = True) -> Self:
         """
@@ -1204,7 +1204,7 @@ def _scatter_by_slice(
                 return self._fill(value, start, stop, inplace=True)
             else:
                 with acquire_spill_lock():
-                    return type(self).from_pylibcudf(  # type: ignore[return-value]
+                    return type(self).from_pylibcudf(
                         plc.copying.copy_range(
                             value.to_pylibcudf(mode="read"),
                             self.to_pylibcudf(mode="read"),
@@ -1315,7 +1315,7 @@ def _validate_fillna_value(
     def replace(
         self, values_to_replace: Self, replacement_values: Self
     ) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.replace.find_and_replace_all(
                 self.to_pylibcudf(mode="read"),
                 values_to_replace.to_pylibcudf(mode="read"),
@@ -1325,7 +1325,7 @@ def replace(
 
     @acquire_spill_lock()
     def repeat(self, repeats: int) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.filling.repeat(
                 plc.Table([self.to_pylibcudf(mode="read")]), repeats
             ).columns()[0]
@@ -1453,7 +1453,7 @@ def interpolate(self, index: Index) -> ColumnBase:
             # Each point is evenly spaced, index values don't matter
             known_x = cp.flatnonzero(valid_locs.values)
         else:
-            known_x = index._column.apply_boolean_mask(valid_locs).values  # type: ignore[attr-defined]
+            known_x = index._column.apply_boolean_mask(valid_locs).values
         known_y = self.apply_boolean_mask(valid_locs).values
 
         result = cp.interp(index.to_cupy(), known_x, known_y)
@@ -2230,7 +2230,7 @@ def one_hot_encode(self, categories: ColumnBase) -> Generator[ColumnBase]:
 
     @acquire_spill_lock()
     def scan(self, scan_op: str, inclusive: bool, **kwargs) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.reduce.scan(
                 self.to_pylibcudf(mode="read"),
                 aggregation.make_aggregation(scan_op, kwargs).plc_obj,
@@ -2602,7 +2602,7 @@ def build_column(
     elif isinstance(dtype, ListDtype):
         return cudf.core.column.ListColumn(
             data=None,
-            size=size,  # type: ignore[arg-type]
+            size=size,
             dtype=dtype,
             mask=mask,
             offset=offset,
@@ -2612,7 +2612,7 @@ def build_column(
     elif isinstance(dtype, IntervalDtype):
         return cudf.core.column.IntervalColumn(
             data=None,
-            size=size,  # type: ignore[arg-type]
+            size=size,
             dtype=dtype,
             mask=mask,
             offset=offset,
@@ -2622,17 +2622,17 @@ def build_column(
     elif isinstance(dtype, StructDtype):
         return cudf.core.column.StructColumn(
             data=None,
-            size=size,  # type: ignore[arg-type]
+            size=size,
             dtype=dtype,
             mask=mask,
             offset=offset,
             null_count=null_count,
-            children=children,  # type: ignore[arg-type]
+            children=children,
         )
     elif isinstance(dtype, cudf.Decimal64Dtype):
         return cudf.core.column.Decimal64Column(
             data=data,  # type: ignore[arg-type]
-            size=size,  # type: ignore[arg-type]
+            size=size,
             offset=offset,
             dtype=dtype,
             mask=mask,
@@ -2642,7 +2642,7 @@ def build_column(
     elif isinstance(dtype, cudf.Decimal32Dtype):
         return cudf.core.column.Decimal32Column(
             data=data,  # type: ignore[arg-type]
-            size=size,  # type: ignore[arg-type]
+            size=size,
             offset=offset,
             dtype=dtype,
             mask=mask,
@@ -2652,7 +2652,7 @@ def build_column(
     elif isinstance(dtype, cudf.Decimal128Dtype):
         return cudf.core.column.Decimal128Column(
             data=data,  # type: ignore[arg-type]
-            size=size,  # type: ignore[arg-type]
+            size=size,
             offset=offset,
             dtype=dtype,
             mask=mask,
@@ -3399,4 +3399,4 @@ def concat_columns(objs: Sequence[ColumnBase]) -> ColumnBase:
             plc.concatenate.concatenate(
                 [col.to_pylibcudf(mode="read") for col in objs_with_len]
             )
-        )._with_type_metadata(objs_with_len[0].dtype)  # type: ignore[return-value]
+        )._with_type_metadata(objs_with_len[0].dtype)
diff --git a/python/cudf/cudf/core/column/datetime.py b/python/cudf/cudf/core/column/datetime.py
index 742ccfc78da..e512b961de2 100644
--- a/python/cudf/cudf/core/column/datetime.py
+++ b/python/cudf/cudf/core/column/datetime.py
@@ -245,7 +245,7 @@ def is_month_end(self) -> ColumnBase:
             last_day_col = type(self).from_pylibcudf(
                 plc.datetime.last_day_of_month(self.to_pylibcudf(mode="read"))
             )
-        return (self.day == last_day_col.day).fillna(False)  # type: ignore[attr-defined]
+        return (self.day == last_day_col.day).fillna(False)
 
     @functools.cached_property
     def is_quarter_end(self) -> ColumnBase:
@@ -564,7 +564,7 @@ def as_string_column(self, dtype: DtypeObj) -> StringColumn:
     def _binaryop(self, other: ColumnBinaryOperand, op: str) -> ColumnBase:
         reflect, op = self._check_reflected_op(op)
         if isinstance(other, cudf.DateOffset):
-            return other._datetime_binop(self, op, reflect=reflect)  # type: ignore[attr-defined]
+            return other._datetime_binop(self, op, reflect=reflect)
         other = self._normalize_binop_operand(other)
         if other is NotImplemented:
             return NotImplemented
@@ -659,10 +659,10 @@ def _binaryop(self, other: ColumnBinaryOperand, op: str) -> ColumnBase:
 
         lhs_binop: plc.Scalar | ColumnBase = (
             pa_scalar_to_plc_scalar(lhs) if isinstance(lhs, pa.Scalar) else lhs
-        )  # type: ignore[assignment]
+        )
         rhs_binop: plc.Scalar | ColumnBase = (
             pa_scalar_to_plc_scalar(rhs) if isinstance(rhs, pa.Scalar) else rhs
-        )  # type: ignore[assignment]
+        )
 
         result_col = binaryop.binaryop(lhs_binop, rhs_binop, op, out_dtype)
         if out_dtype.kind != "b" and op == "__add__":
@@ -679,11 +679,11 @@ def _with_type_metadata(self, dtype: DtypeObj) -> DatetimeColumn:
             return DatetimeTZColumn(
                 data=self.base_data,  # type: ignore[arg-type]
                 dtype=dtype,
-                mask=self.base_mask,  # type: ignore[arg-type]
+                mask=self.base_mask,
                 size=self.size,
                 offset=self.offset,
                 null_count=self.null_count,
-                children=self.base_children,  # type: ignore[arg-type]
+                children=self.base_children,
             )
         if cudf.get_option("mode.pandas_compatible"):
             self._dtype = get_dtype_of_same_type(dtype, self.dtype)
@@ -847,11 +847,11 @@ def _utc_time(self) -> DatetimeColumn:
         return DatetimeColumn(
             data=self.base_data,  # type: ignore[arg-type]
             dtype=_get_base_dtype(self.dtype),
-            mask=self.base_mask,  # type: ignore[arg-type]
+            mask=self.base_mask,
             size=self.size,
             offset=self.offset,
             null_count=self.null_count,
-            children=self.base_children,  # type: ignore[arg-type]
+            children=self.base_children,
         )
 
     @functools.cached_property
diff --git a/python/cudf/cudf/core/column/decimal.py b/python/cudf/cudf/core/column/decimal.py
index e22cdfc3766..f546ea5c204 100644
--- a/python/cudf/cudf/core/column/decimal.py
+++ b/python/cudf/cudf/core/column/decimal.py
@@ -254,7 +254,7 @@ def _binaryop(self, other: ColumnBinaryOperand, op: str) -> ColumnBase:
                     other = other.astype(self.dtype)
             other_cudf_dtype = other.dtype
         elif isinstance(other, (int, Decimal)):
-            other_cudf_dtype = self.dtype._from_decimal(Decimal(other))  # type: ignore[arg-type, union-attr]
+            other_cudf_dtype = self.dtype._from_decimal(Decimal(other))  # type: ignore[union-attr]
         elif isinstance(other, float):
             return self._binaryop(as_column(other, length=len(self)), op)
         elif is_na_like(other):
diff --git a/python/cudf/cudf/core/column/interval.py b/python/cudf/cudf/core/column/interval.py
index 0906119eca9..a67cf6a3904 100644
--- a/python/cudf/cudf/core/column/interval.py
+++ b/python/cudf/cudf/core/column/interval.py
@@ -29,7 +29,7 @@ def __init__(
         mask: Buffer | None,
         offset: int,
         null_count: int,
-        children: tuple[ColumnBase, ColumnBase],  # type: ignore[assignment]
+        children: tuple[ColumnBase, ColumnBase],
     ):
         if len(children) != 2:
             raise ValueError(
@@ -129,7 +129,7 @@ def set_closed(
             IntervalDtype(self.dtype.subtype, closed)  # type: ignore[union-attr]
         )
 
-    def as_interval_column(self, dtype: IntervalDtype) -> Self:  # type: ignore[override]
+    def as_interval_column(self, dtype: IntervalDtype) -> Self:
         if isinstance(dtype, IntervalDtype):
             return self._with_type_metadata(dtype)  # type: ignore[return-value]
         else:
@@ -159,7 +159,7 @@ def to_pandas(
 
     def element_indexing(
         self, index: int
-    ) -> pd.Interval | dict[Any, Any] | None:  # type: ignore[override]
+    ) -> pd.Interval | dict[Any, Any] | None:
         result = super().element_indexing(index)
         if isinstance(result, dict) and cudf.get_option(
             "mode.pandas_compatible"
diff --git a/python/cudf/cudf/core/column/lists.py b/python/cudf/cudf/core/column/lists.py
index 40b2ee92496..c01122a0bbf 100644
--- a/python/cudf/cudf/core/column/lists.py
+++ b/python/cudf/cudf/core/column/lists.py
@@ -49,7 +49,7 @@ def __init__(
         mask: Buffer | None,
         offset: int,
         null_count: int,
-        children: tuple[NumericalColumn, ColumnBase],  # type: ignore[assignment]
+        children: tuple[NumericalColumn, ColumnBase],
     ):
         if data is not None:
             raise ValueError("data must be None")
@@ -156,7 +156,7 @@ def _binaryop(self, other: ColumnBinaryOperand, op: str) -> ColumnBase:
             return NotImplemented
         if isinstance(other.dtype, ListDtype):
             if op == "__add__":
-                return self.concatenate_rows([other])  # type: ignore[list-item]
+                return self.concatenate_rows([other])
             else:
                 raise NotImplementedError(
                     "Lists concatenation for this operation is not yet"
@@ -287,7 +287,7 @@ def from_sequences(cls, arbitrary: Sequence[ColumnLike]) -> Self:
             0,
             [offset_col, data_plc_col],
         )
-        return cls.from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return cls.from_pylibcudf(plc_column)
 
     @cached_property
     def _string_separators(self) -> plc.Column:
@@ -537,7 +537,7 @@ def minhash_ngrams(
                     f"seed must be in range [0, {np.iinfo(np.uint32).max}]"
                 )
             seed = np.uint32(seed)
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.minhash.minhash_ngrams(
                 self.to_pylibcudf(mode="read"),
                 width,
@@ -562,7 +562,7 @@ def minhash64_ngrams(
                     f"seed must be in range [0, {np.iinfo(np.uint64).max}]"
                 )
             seed = np.uint64(seed)
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.minhash.minhash64_ngrams(
                 self.to_pylibcudf(mode="read"),
                 width,
diff --git a/python/cudf/cudf/core/column/numerical.py b/python/cudf/cudf/core/column/numerical.py
index 6c793d6416b..176e695cc74 100644
--- a/python/cudf/cudf/core/column/numerical.py
+++ b/python/cudf/cudf/core/column/numerical.py
@@ -352,7 +352,7 @@ def _binaryop(self, other: ColumnBinaryOperand, op: str) -> ColumnBase:
         )
         rhs_binaryop: plc.Scalar | ColumnBase = (
             pa_scalar_to_plc_scalar(rhs) if isinstance(rhs, pa.Scalar) else rhs
-        )  # type: ignore[assignment]
+        )
 
         res = binaryop.binaryop(lhs_binaryop, rhs_binaryop, op, out_dtype)
         if (
@@ -556,9 +556,9 @@ def as_numerical_column(self, dtype: Dtype) -> NumericalColumn:
             if (
                 not is_pandas_nullable_extension_dtype(self.dtype)
                 and is_pandas_nullable_extension_dtype(dtype)
-                and dtype.kind == "f"  # type: ignore[union-attr]
+                and dtype.kind == "f"
             ):
-                res = self.nans_to_nulls().cast(dtype=dtype)  # type: ignore[return-value]
+                res = self.nans_to_nulls().cast(dtype=dtype)
                 res._dtype = dtype
                 return res  # type: ignore[return-value]
             if dtype_to_pylibcudf_type(dtype) == dtype_to_pylibcudf_type(
@@ -588,7 +588,7 @@ def as_numerical_column(self, dtype: Dtype) -> NumericalColumn:
                         "Cannot convert non-finite values (NA or inf) to integer"
                     )
                 # If casting from float to int, we need to convert nans to nulls
-                res = self.nans_to_nulls().cast(dtype=dtype)  # type: ignore[return-value]
+                res = self.nans_to_nulls().cast(dtype=dtype)
                 res._dtype = dtype
                 return res  # type: ignore[return-value]
 
@@ -767,7 +767,7 @@ def _validate_fillna_value(
             return super()._validate_fillna_value(fill_value)
         else:
             cudf_obj = as_column(fill_value, nan_as_null=False)
-            if not cudf_obj.can_cast_safely(self.dtype):  # type: ignore[attr-defined]
+            if not cudf_obj.can_cast_safely(self.dtype):
                 raise TypeError(
                     f"Cannot safely cast non-equivalent "
                     f"{cudf_obj.dtype.type.__name__} to "
@@ -963,7 +963,7 @@ def digitize(self, bins: np.ndarray, right: bool = False) -> Self:
         if bin_col.nullable:
             raise ValueError("`bins` cannot contain null entries.")
 
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             getattr(plc.search, "lower_bound" if right else "upper_bound")(
                 plc.Table([bin_col.to_pylibcudf(mode="read")]),
                 plc.Table([self.to_pylibcudf(mode="read")]),
diff --git a/python/cudf/cudf/core/column/numerical_base.py b/python/cudf/cudf/core/column/numerical_base.py
index 7d9c4ce0831..e2263bd5850 100644
--- a/python/cudf/cudf/core/column/numerical_base.py
+++ b/python/cudf/cudf/core/column/numerical_base.py
@@ -164,7 +164,7 @@ def quantile(
                     indices.to_pylibcudf(mode="read"),
                     exact,
                 )
-                result = type(self).from_pylibcudf(plc_column)  # type: ignore[assignment]
+                result = type(self).from_pylibcudf(plc_column)
         if return_scalar:
             scalar_result = result.element_indexing(0)
             if interpolation in {"lower", "higher", "nearest"}:
@@ -268,7 +268,7 @@ def round(
             raise ValueError(f"{how=} must be either 'half_even' or 'half_up'")
         plc_how = plc.round.RoundingMethod[how.upper()]
         with acquire_spill_lock():
-            return type(self).from_pylibcudf(  # type: ignore[return-value]
+            return type(self).from_pylibcudf(
                 plc.round.round(
                     self.to_pylibcudf(mode="read"), decimals, plc_how
                 )
diff --git a/python/cudf/cudf/core/column/string.py b/python/cudf/cudf/core/column/string.py
index 952a815273e..47222d03bbb 100644
--- a/python/cudf/cudf/core/column/string.py
+++ b/python/cudf/cudf/core/column/string.py
@@ -123,7 +123,7 @@ def __init__(
         mask: Buffer | None,
         offset: int,
         null_count: int,
-        children: tuple[ColumnBase],  # type: ignore[assignment]
+        children: tuple[ColumnBase],
     ):
         if not isinstance(data, Buffer):
             raise ValueError("data must be a Buffer")
@@ -332,7 +332,7 @@ def as_numerical_column(self, dtype: np.dtype) -> NumericalColumn:
             result = self.count_characters() > np.int8(0)
             if not is_pandas_nullable_extension_dtype(dtype):
                 result = result.fillna(False)
-            return result._with_type_metadata(dtype)  # type: ignore[return-value]
+            return result._with_type_metadata(dtype)
 
         cast_func: Callable[[plc.Column, plc.DataType], plc.Column]
         if dtype.kind in {"i", "u"}:
@@ -678,7 +678,7 @@ def generate_ngrams(self, ngrams: int, separator: plc.Scalar) -> Self:
             ngrams,
             separator,
         )
-        return type(self).from_pylibcudf(result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(result)
 
     @acquire_spill_lock()
     def generate_character_ngrams(self, ngrams: int) -> ListColumn:
@@ -708,7 +708,7 @@ def build_suffix_array(self, min_width: int) -> Self:
         result = plc.nvtext.deduplicate.build_suffix_array(
             self.to_pylibcudf(mode="read"), min_width
         )
-        return type(self).from_pylibcudf(result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(result)
 
     @acquire_spill_lock()
     def resolve_duplicates(self, sa: Self, min_width: int) -> Self:
@@ -717,7 +717,7 @@ def resolve_duplicates(self, sa: Self, min_width: int) -> Self:
             sa.to_pylibcudf(mode="read"),
             min_width,
         )
-        return type(self).from_pylibcudf(result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(result)
 
     @acquire_spill_lock()
     def resolve_duplicates_pair(
@@ -730,7 +730,7 @@ def resolve_duplicates_pair(
             sa2.to_pylibcudf(mode="read"),
             min_width,
         )
-        return type(self).from_pylibcudf(result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(result)
 
     @acquire_spill_lock()
     def edit_distance(self, targets: Self) -> NumericalColumn:
@@ -752,7 +752,7 @@ def byte_pair_encoding(
         merge_pairs: plc.nvtext.byte_pair_encode.BPEMergePairs,
         separator: str,
     ) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.byte_pair_encode.byte_pair_encoding(
                 self.to_pylibcudf(mode="read"),
                 merge_pairs,
@@ -767,7 +767,7 @@ def ngrams_tokenize(
         delimiter: plc.Scalar,
         separator: plc.Scalar,
     ) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.ngrams_tokenize.ngrams_tokenize(
                 self.to_pylibcudf(mode="read"),
                 ngrams,
@@ -778,7 +778,7 @@ def ngrams_tokenize(
 
     @acquire_spill_lock()
     def normalize_spaces(self) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.normalize.normalize_spaces(
                 self.to_pylibcudf(mode="read")
             )
@@ -799,7 +799,7 @@ def normalize_characters(
     def replace_tokens(
         self, targets: Self, replacements: Self, delimiter: plc.Scalar
     ) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.replace.replace_tokens(
                 self.to_pylibcudf(mode="read"),
                 targets.to_pylibcudf(mode="read"),
@@ -815,7 +815,7 @@ def filter_tokens(
         replacement: plc.Scalar,
         delimiter: plc.Scalar,
     ) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.replace.filter_tokens(
                 self.to_pylibcudf(mode="read"),
                 min_token_length,
@@ -834,7 +834,7 @@ def porter_stemmer_measure(self) -> NumericalColumn:
 
     @acquire_spill_lock()
     def is_letter(self, is_vowel: bool, index: int | NumericalColumn) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.stemmer.is_letter(
                 self.to_pylibcudf(mode="read"),
                 is_vowel,
@@ -846,7 +846,7 @@ def is_letter(self, is_vowel: bool, index: int | NumericalColumn) -> Self:
 
     @acquire_spill_lock()
     def tokenize_scalar(self, delimiter: plc.Scalar) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.tokenize.tokenize_scalar(
                 self.to_pylibcudf(mode="read"), delimiter
             )
@@ -854,7 +854,7 @@ def tokenize_scalar(self, delimiter: plc.Scalar) -> Self:
 
     @acquire_spill_lock()
     def tokenize_column(self, delimiters: Self) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.tokenize.tokenize_column(
                 self.to_pylibcudf(mode="read"),
                 delimiters.to_pylibcudf(mode="read"),
@@ -880,7 +880,7 @@ def count_tokens_column(self, delimiters: Self) -> NumericalColumn:
 
     @acquire_spill_lock()
     def character_tokenize(self) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.tokenize.character_tokenize(
                 self.to_pylibcudf(mode="read")
             )
@@ -893,7 +893,7 @@ def tokenize_with_vocabulary(
         delimiter: str,
         default_id: int,
     ) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.tokenize.tokenize_with_vocabulary(
                 self.to_pylibcudf(mode="read"),
                 vocabulary,
@@ -908,7 +908,7 @@ def wordpiece_tokenize(
         vocabulary: plc.nvtext.wordpiece_tokenize.WordPieceVocabulary,
         max_words_per_row: int,
     ) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.wordpiece_tokenize.wordpiece_tokenize(
                 self.to_pylibcudf(mode="read"),
                 vocabulary,
@@ -918,7 +918,7 @@ def wordpiece_tokenize(
 
     @acquire_spill_lock()
     def detokenize(self, indices: ColumnBase, separator: plc.Scalar) -> Self:
-        return type(self).from_pylibcudf(  # type: ignore[return-value]
+        return type(self).from_pylibcudf(
             plc.nvtext.tokenize.detokenize(
                 self.to_pylibcudf(mode="read"),
                 indices.to_pylibcudf(mode="read"),
@@ -1080,7 +1080,7 @@ def _split_record(
             delimiter,
             maxsplit,
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     def split_record(self, delimiter: plc.Scalar, maxsplit: int) -> Self:
         return self._split_record(
@@ -1149,14 +1149,14 @@ def url_decode(self) -> Self:
         plc_column = plc.strings.convert.convert_urls.url_decode(
             self.to_pylibcudf(mode="read")
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def url_encode(self) -> Self:
         plc_column = plc.strings.convert.convert_urls.url_encode(
             self.to_pylibcudf(mode="read")
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def is_integer(self) -> NumericalColumn:
@@ -1193,7 +1193,7 @@ def join_strings(self, separator: str, na_rep: str | None) -> Self:
             pa_scalar_to_plc_scalar(pa.scalar(separator)),
             pa_scalar_to_plc_scalar(pa.scalar(na_rep, type=pa.string())),
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def concatenate(
@@ -1209,7 +1209,7 @@ def concatenate(
             pa_scalar_to_plc_scalar(pa.scalar(sep)),
             pa_scalar_to_plc_scalar(pa.scalar(na_rep, type=pa.string())),
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def extract(self, pattern: str, flags: int) -> dict[int, Self]:
@@ -1235,7 +1235,7 @@ def contains_re(self, pattern: str, flags: int) -> Self:
                 plc_flags_from_re_flags(flags),
             ),
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def str_contains(self, pattern: str | Self) -> Self:
@@ -1248,7 +1248,7 @@ def str_contains(self, pattern: str | Self) -> Self:
             self.to_pylibcudf(mode="read"),
             plc_pattern,
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def like(self, pattern: str, escape: str) -> Self:
@@ -1257,7 +1257,7 @@ def like(self, pattern: str, escape: str) -> Self:
             pa_scalar_to_plc_scalar(pa.scalar(pattern)),
             pa_scalar_to_plc_scalar(pa.scalar(escape)),
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def repeat_strings(self, repeats: int | ColumnBase) -> Self:
@@ -1270,7 +1270,7 @@ def repeat_strings(self, repeats: int | ColumnBase) -> Self:
             self.to_pylibcudf(mode="read"),
             plc_repeats,
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def replace_re(
@@ -1298,7 +1298,7 @@ def replace_re(
             )
         else:
             raise ValueError("Invalid pattern and replacement types")
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def replace_str(
@@ -1310,7 +1310,7 @@ def replace_str(
             pa_scalar_to_plc_scalar(replacement),
             max_replace_count,
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def replace_with_backrefs(self, pattern: str, replacement: str) -> Self:
@@ -1321,7 +1321,7 @@ def replace_with_backrefs(self, pattern: str, replacement: str) -> Self:
             ),
             replacement,
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def slice_strings(
@@ -1352,7 +1352,7 @@ def slice_strings(
         plc_result = plc.strings.slice.slice_strings(
             self.to_pylibcudf(mode="read"), plc_start, plc_stop, plc_step
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def all_characters_of_type(
@@ -1378,7 +1378,7 @@ def filter_characters_of_type(
             pa_scalar_to_plc_scalar(pa.scalar(replacement, type=pa.string())),
             types_to_keep,
         )
-        return type(self).from_pylibcudf(plc_column)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_column)
 
     @acquire_spill_lock()
     def replace_slice(self, start: int, stop: int, repl: str) -> Self:
@@ -1388,7 +1388,7 @@ def replace_slice(self, start: int, stop: int, repl: str) -> Self:
             start,
             stop,
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def get_json_object(
@@ -1410,7 +1410,7 @@ def get_json_object(
             pa_scalar_to_plc_scalar(pa.scalar(json_path)),
             options,
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def pad(
@@ -1422,7 +1422,7 @@ def pad(
             side,
             fillchar,
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def zfill(self, width: int) -> Self:
@@ -1430,7 +1430,7 @@ def zfill(self, width: int) -> Self:
             self.to_pylibcudf(mode="read"),
             width,
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def strip(
@@ -1443,7 +1443,7 @@ def strip(
                 pa.scalar(to_strip or "", type=pa.string())
             ),
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def wrap(self, width: int) -> Self:
@@ -1451,7 +1451,7 @@ def wrap(self, width: int) -> Self:
             self.to_pylibcudf(mode="read"),
             width,
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def count_re(self, pattern: str, flags: int) -> NumericalColumn:
@@ -1478,7 +1478,7 @@ def findall(
                 pat, plc_flags_from_re_flags(flags)
             ),
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def find_multiple(self, patterns: Self) -> Self:
@@ -1486,7 +1486,7 @@ def find_multiple(self, patterns: Self) -> Self:
             self.to_pylibcudf(mode="read"),
             patterns.to_pylibcudf(mode="read"),
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def starts_ends_with(
@@ -1518,7 +1518,7 @@ def starts_ends_with(
             raise TypeError(
                 f"expected a str or tuple[str, ...], not {type(pat).__name__}"
             )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def find(
@@ -1534,7 +1534,7 @@ def find(
             start,
             end,
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def matches_re(self, pattern: str, flags: int) -> Self:
@@ -1544,14 +1544,14 @@ def matches_re(self, pattern: str, flags: int) -> Self:
                 pattern, plc_flags_from_re_flags(flags)
             ),
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def code_points(self) -> Self:
         plc_result = plc.strings.attributes.code_points(
             self.to_pylibcudf(mode="read"),
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def translate(self, table: dict) -> Self:
@@ -1559,7 +1559,7 @@ def translate(self, table: dict) -> Self:
             self.to_pylibcudf(mode="read"),
             str.maketrans(table),  # type: ignore[arg-type]
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
 
     @acquire_spill_lock()
     def filter_characters(
@@ -1576,4 +1576,4 @@ def filter_characters(
             else plc.strings.translate.FilterType.REMOVE,
             pa_scalar_to_plc_scalar(pa.scalar(repl, type=pa.string())),
         )
-        return type(self).from_pylibcudf(plc_result)  # type: ignore[return-value]
+        return type(self).from_pylibcudf(plc_result)
diff --git a/python/cudf/cudf/core/column/struct.py b/python/cudf/cudf/core/column/struct.py
index ae27c97985e..49e685cd5fe 100644
--- a/python/cudf/cudf/core/column/struct.py
+++ b/python/cudf/cudf/core/column/struct.py
@@ -210,7 +210,7 @@ def _with_type_metadata(
                 null_count=self.null_count,
                 children=tuple(  # type: ignore[arg-type]
                     child.astype(dtype.subtype) for child in self.base_children
-                ),  # type: ignore[arg-type]
+                ),
             )
         elif isinstance(dtype, StructDtype):
             return StructColumn(
diff --git a/python/cudf/cudf/core/column/temporal_base.py b/python/cudf/cudf/core/column/temporal_base.py
index 8ae4f8b7e6e..dc3a912b3ac 100644
--- a/python/cudf/cudf/core/column/temporal_base.py
+++ b/python/cudf/cudf/core/column/temporal_base.py
@@ -309,7 +309,7 @@ def find_and_replace(
             return self.copy(deep=True)
 
     def can_cast_safely(self, to_dtype: DtypeObj) -> bool:
-        if to_dtype.kind == self.dtype.kind:  # type: ignore[union-attr]
+        if to_dtype.kind == self.dtype.kind:
             to_res, _ = np.datetime_data(to_dtype)
             # call-overload must be ignored because numpy stubs only accept literal strings
             # for time units (e.g., "ns", "us") to allow compile-time validation,
diff --git a/python/cudf/cudf/core/column/timedelta.py b/python/cudf/cudf/core/column/timedelta.py
index dacd4e866cf..7662e755fa1 100644
--- a/python/cudf/cudf/core/column/timedelta.py
+++ b/python/cudf/cudf/core/column/timedelta.py
@@ -275,7 +275,7 @@ def sum(
             # Since sum isn't overridden in Numerical[Base]Column, mypy only
             # sees the signature from Reducible (which doesn't have the extra
             # parameters from ColumnBase._reduce) so we have to ignore this.
-            self.astype(self._UNDERLYING_DTYPE).sum(  # type: ignore
+            self.astype(self._UNDERLYING_DTYPE).sum(  # type: ignore[call-arg]
                 skipna=skipna, min_count=min_count
             ),
             unit=self.time_unit,
diff --git a/python/cudf/cudf/core/dataframe.py b/python/cudf/cudf/core/dataframe.py
index ec5758ffdd5..bb668afa554 100644
--- a/python/cudf/cudf/core/dataframe.py
+++ b/python/cudf/cudf/core/dataframe.py
@@ -1633,7 +1633,7 @@ def __delitem__(self, name):
         self._drop_column(name)
 
     @_performance_tracking
-    def memory_usage(self, index: bool = True, deep: bool = False) -> Series:  # type: ignore[override]
+    def memory_usage(self, index: bool = True, deep: bool = False) -> Series:
         """
         Return the memory usage of the DataFrame.
 
@@ -2600,7 +2600,7 @@ def to_dict(
             # Special case needed to avoid converting
             # Series objects into pd.Series
             if not inspect.isclass(into):
-                cons = type(into)  # type: ignore[assignment]
+                cons = type(into)
                 if isinstance(into, defaultdict):
                     cons = functools.partial(cons, into.default_factory)
             elif issubclass(into, Mapping):
@@ -2846,7 +2846,7 @@ def at(self):
         """
         return _DataFrameAtIndexer(self)
 
-    @property  # type: ignore
+    @property
     @_external_only_api(
         "Use _column_names instead, or _data.to_pandas_index if a pandas "
         "index is absolutely necessary. For checking if the columns are a "
@@ -2857,7 +2857,7 @@ def columns(self):
         """Returns a tuple of columns"""
         return self._data.to_pandas_index
 
-    @columns.setter  # type: ignore
+    @columns.setter
     @_performance_tracking
     def columns(self, columns):
         multiindex = False
@@ -3550,7 +3550,7 @@ def _insert(self, loc, name, value, nan_as_null=None, ignore_index=True):
         value = as_column(value, nan_as_null=nan_as_null)
         self._data.insert(name, value, loc=loc)
 
-    @property  # type:ignore
+    @property
     @_performance_tracking
     def axes(self):
         """
diff --git a/python/cudf/cudf/core/dtypes.py b/python/cudf/cudf/core/dtypes.py
index 3215d95f427..b74e5a78979 100644
--- a/python/cudf/cudf/core/dtypes.py
+++ b/python/cudf/cudf/core/dtypes.py
@@ -1048,7 +1048,7 @@ def from_pandas(cls, pd_dtype: pd.IntervalDtype) -> Self:
     def to_pandas(self) -> pd.IntervalDtype:
         if cudf.get_option("mode.pandas_compatible"):
             return pd.IntervalDtype(
-                subtype=self.subtype.numpy_dtype  # type: ignore
+                subtype=self.subtype.numpy_dtype
                 if is_pandas_nullable_extension_dtype(self.subtype)
                 else self.subtype,
                 closed=self.closed,
diff --git a/python/cudf/cudf/core/frame.py b/python/cudf/cudf/core/frame.py
index 60dca874a3a..7f39133ae1c 100644
--- a/python/cudf/cudf/core/frame.py
+++ b/python/cudf/cudf/core/frame.py
@@ -636,8 +636,7 @@ def to_array(
                     col.has_nulls() for col in self._columns
                 ):
                     if to_dtype.kind == "b" or any(
-                        dtype.kind == "b"  # type: ignore[union-attr]
-                        for _, dtype in self._dtypes
+                        dtype.kind == "b" for _, dtype in self._dtypes
                     ):
                         if module == cupy:
                             raise ValueError(
diff --git a/python/cudf/cudf/core/groupby/groupby.py b/python/cudf/cudf/core/groupby/groupby.py
index ce878857b35..bde1f0bf814 100644
--- a/python/cudf/cudf/core/groupby/groupby.py
+++ b/python/cudf/cudf/core/groupby/groupby.py
@@ -1365,7 +1365,7 @@ def nth(self, n, dropna: Literal["any", "all", None] = None):
         """
         if dropna is not None:
             raise NotImplementedError("dropna is not currently supported.")
-        self.obj["__groupbynth_order__"] = range(0, len(self.obj))  # type: ignore[index]
+        self.obj["__groupbynth_order__"] = range(0, len(self.obj))
         # We perform another groupby here to have the grouping columns
         # be a part of dataframe columns.
         result = self.obj.groupby(self.grouping.keys).agg(lambda x: x.nth(n))
@@ -1734,7 +1734,7 @@ def _raise_invalid_type(x):
         # seems because unlike the builtin narrowings it only performs
         # narrowing in the positive case.
         normalized_aggs = [
-            list(agg) if is_list_like(agg) else [agg]  # type: ignore
+            list(agg) if is_list_like(agg) else [agg]  # type: ignore[arg-type]
             for agg in aggs_per_column
         ]
         return column_names, columns, normalized_aggs
diff --git a/python/cudf/cudf/core/index.py b/python/cudf/cudf/core/index.py
index c0ea6d7b105..7b9638c0496 100644
--- a/python/cudf/cudf/core/index.py
+++ b/python/cudf/cudf/core/index.py
@@ -175,7 +175,7 @@ def validate_range_arg(arg, arg_name: Literal["start", "stop", "step"]) -> int:
     return int(arg)
 
 
-class Index(SingleColumnFrame):  # type: ignore[misc]
+class Index(SingleColumnFrame):
     """
     Immutable sequence used for indexing and alignment.
 
@@ -1909,7 +1909,7 @@ def inferred_type(self) -> str:
     def memory_usage(self, deep: bool = False) -> int:
         return self._column.memory_usage
 
-    @cached_property  # type: ignore
+    @cached_property  # type: ignore[explicit-override]
     @_performance_tracking
     def is_unique(self) -> bool:
         return self._column.is_unique
@@ -3183,7 +3183,7 @@ def _try_reconstruct_range_index(self, index: Index) -> Self | Index:
             return index
         # Evenly spaced values can return a
         # RangeIndex instead of a materialized Index.
-        if not index._column.has_nulls():  # type: ignore[attr-defined]
+        if not index._column.has_nulls():
             uniques = cupy.unique(cupy.diff(index.values))
             if len(uniques) == 1 and (diff := uniques[0].get()) != 0:
                 new_range = range(index[0], index[-1] + diff, diff)
@@ -5237,7 +5237,7 @@ def __init__(
             )
 
         if dtype:
-            interval_col = interval_col.astype(dtype)  # type: ignore[assignment]
+            interval_col = interval_col.astype(dtype)
 
         SingleColumnFrame.__init__(
             self, ColumnAccessor({name: interval_col}, verify=False)
@@ -5371,7 +5371,7 @@ def from_tuples(
         pidx = pd.IntervalIndex.from_tuples(
             data, closed=closed, name=name, copy=copy, dtype=dtype
         )
-        return cls(pidx, name=name)  # type: ignore[return-value]
+        return cls(pidx, name=name)
 
     def __getitem__(self, index):
         raise NotImplementedError(
diff --git a/python/cudf/cudf/core/indexed_frame.py b/python/cudf/cudf/core/indexed_frame.py
index f6657e773ea..0714e41915a 100644
--- a/python/cudf/cudf/core/indexed_frame.py
+++ b/python/cudf/cudf/core/indexed_frame.py
@@ -266,8 +266,8 @@ class IndexedFrame(Frame):
     """
 
     # mypy can't handle bound type variables as class members
-    _loc_indexer_type: type[_LocIndexerClass]  # type: ignore
-    _iloc_indexer_type: type[_IlocIndexerClass]  # type: ignore
+    _loc_indexer_type: type[_LocIndexerClass]  # type: ignore[valid-type]
+    _iloc_indexer_type: type[_IlocIndexerClass]  # type: ignore[valid-type]
     _groupby = GroupBy
     _resampler = _Resampler
 
@@ -353,7 +353,7 @@ def attrs(self, value: Mapping[Hashable, Any]) -> None:
         self._attrs = dict(value)
 
     @classmethod
-    def _from_data(  # type: ignore[override]
+    def _from_data(
         cls,
         data: MutableMapping,
         index: Index | None = None,
@@ -2440,7 +2440,7 @@ def iloc(self):
         """
         return self._iloc_indexer_type(self)
 
-    @property  # type:ignore
+    @property
     @_performance_tracking
     def axes(self):
         """
@@ -6459,7 +6459,7 @@ def rank(
         if numeric_only:
             if isinstance(source, cudf.Series) and not is_dtype_obj_numeric(
                 source.dtype, include_decimal=False
-            ):  # type: ignore[attr-defined]
+            ):
                 raise TypeError(
                     "Series.rank does not allow numeric_only=True with "
                     "non-numeric dtype."
@@ -6833,7 +6833,7 @@ def _drop_rows_by_labels(
             level = 0
 
         levels_index = obj.index.get_level_values(level)
-        if errors == "raise" and not labels.isin(levels_index).all():  # type: ignore[union-attr]
+        if errors == "raise" and not labels.isin(levels_index).all():
             raise KeyError("One or more values not found in axis")
 
         if isinstance(level, int):
@@ -6888,7 +6888,7 @@ def _drop_rows_by_labels(
 
     else:
         orig_index_type = obj.index.dtype
-        if errors == "raise" and not labels.isin(obj.index).all():  # type: ignore[union-attr]
+        if errors == "raise" and not labels.isin(obj.index).all():
             raise KeyError("One or more values not found in axis")
 
         if isinstance(labels, ColumnBase):
diff --git a/python/cudf/cudf/core/multiindex.py b/python/cudf/cudf/core/multiindex.py
index 6d0e4a3c683..49f85a96571 100644
--- a/python/cudf/cudf/core/multiindex.py
+++ b/python/cudf/cudf/core/multiindex.py
@@ -239,12 +239,12 @@ def __init__(
         self._name = None
         self.names = names
 
-    @property  # type: ignore
+    @property  # type: ignore[explicit-override]
     @_performance_tracking
     def names(self):
         return self._names
 
-    @names.setter  # type: ignore
+    @names.setter
     @_performance_tracking
     def names(self, value):
         if value is None:
@@ -370,7 +370,7 @@ def set_names(
             existing_names[lev] = names[i]
         names = existing_names
 
-        return self._set_names(names=names, inplace=inplace)  # type: ignore[return-value]
+        return self._set_names(names=names, inplace=inplace)
 
     def _maybe_materialize_codes_and_levels(self: Self) -> Self:
         """
@@ -443,12 +443,12 @@ def _simple_new(
         mi._name = name
         return mi
 
-    @property  # type: ignore
+    @property  # type: ignore[explicit-override]
     @_performance_tracking
     def name(self):
         return self._name
 
-    @name.setter  # type: ignore
+    @name.setter
     @_performance_tracking
     def name(self, value):
         self._name = value
@@ -577,7 +577,7 @@ def __repr__(self) -> str:
         data_output = "\n".join(lines)
         return output_prefix + data_output
 
-    @property  # type: ignore
+    @property
     @_external_only_api("Use ._codes instead")
     @_performance_tracking
     def codes(self) -> pd.core.indexes.frozen.FrozenList:
@@ -608,7 +608,7 @@ def get_slice_bound(self, label, side):
             "get_slice_bound is not currently implemented."
         )
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def levels(self) -> list[cudf.Index]:
         """
@@ -642,7 +642,7 @@ def levels(self) -> list[cudf.Index]:
             for idx, name in zip(self._levels, self.names, strict=True)  # type: ignore[arg-type]
         ]
 
-    @property  # type: ignore
+    @property  # type: ignore[explicit-override]
     @_performance_tracking
     def ndim(self) -> int:
         """Dimension of the data. For MultiIndex ndim is always 2."""
@@ -974,7 +974,7 @@ def __eq__(self, other):
             )
         return NotImplemented
 
-    @property  # type: ignore
+    @property  # type: ignore[explicit-override]
     @_performance_tracking
     def size(self) -> int:
         # The size of a MultiIndex is only dependent on the number of rows.
@@ -1760,7 +1760,7 @@ def from_pandas(
             nan_as_null=nan_as_null,
         )
 
-    @cached_property  # type: ignore
+    @cached_property  # type: ignore[explicit-override]
     @_performance_tracking
     def is_unique(self) -> bool:
         return len(self) == self.nunique(dropna=False)
diff --git a/python/cudf/cudf/core/series.py b/python/cudf/cudf/core/series.py
index d9f3f065b3f..d693d4dab1c 100644
--- a/python/cudf/cudf/core/series.py
+++ b/python/cudf/cudf/core/series.py
@@ -684,7 +684,7 @@ def from_pandas(cls, s: pd.Series, nan_as_null=no_default):
             result = cls(s, nan_as_null=nan_as_null)
         return result
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_unique(self):
         """Return boolean if values in the object are unique.
@@ -695,7 +695,7 @@ def is_unique(self):
         """
         return self._column.is_unique
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def dt(self):
         """
@@ -740,7 +740,7 @@ def dt(self):
                 "Can only use .dt accessor with datetimelike values"
             )
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def hasnans(self):
         """
@@ -1054,7 +1054,7 @@ def to_frame(self, name: Hashable = no_default) -> DataFrame:
         return res
 
     @_performance_tracking
-    def memory_usage(self, index: bool = True, deep: bool = False) -> int:  # type: ignore[override]
+    def memory_usage(self, index: bool = True, deep: bool = False) -> int:
         """
         Return the memory usage of the Series.
 
@@ -1452,31 +1452,31 @@ def _make_operands_and_index_for_binop(
         operands = lhs._make_operands_for_binop(other, fill_value, reflect)
         return operands, lhs.index, ca_attributes
 
-    @copy_docstring(CategoricalAccessor)  # type: ignore
+    @copy_docstring(CategoricalAccessor)  # type: ignore[prop-decorator]
     @property
     @_performance_tracking
     def cat(self):
         return CategoricalAccessor(parent=self)
 
-    @copy_docstring(StringMethods)  # type: ignore
+    @copy_docstring(StringMethods)  # type: ignore[prop-decorator]
     @property
     @_performance_tracking
     def str(self):
         return StringMethods(parent=self)
 
-    @copy_docstring(ListMethods)  # type: ignore
+    @copy_docstring(ListMethods)  # type: ignore[prop-decorator]
     @property
     @_performance_tracking
     def list(self):
         return ListMethods(parent=self)
 
-    @copy_docstring(StructMethods)  # type: ignore
+    @copy_docstring(StructMethods)  # type: ignore[prop-decorator]
     @property
     @_performance_tracking
     def struct(self):
         return StructMethods(parent=self)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def dtypes(self):
         """The dtype of the Series.
@@ -1545,19 +1545,19 @@ def _concat(cls, objs, axis=0, index: bool = True):
 
         return cls._from_column(col, name=name, index=result_index)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def valid_count(self):
         """Number of non-null values"""
         return len(self) - self._column.null_count
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def null_count(self):
         """Number of null values"""
         return self._column.null_count
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def has_nulls(self):
         """
@@ -1967,7 +1967,7 @@ def to_pandas(
         res.attrs = self.attrs
         return res
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def data(self):
         """The gpu buffer for the data
@@ -3948,7 +3948,7 @@ class DatetimeProperties(BaseDatelikeProperties):
     dtype: int16
     """
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def year(self) -> Series:
         """
@@ -3973,7 +3973,7 @@ def year(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.year)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def month(self) -> Series:
         """
@@ -3998,7 +3998,7 @@ def month(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.month)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def day(self) -> Series:
         """
@@ -4023,7 +4023,7 @@ def day(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.day)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def hour(self) -> Series:
         """
@@ -4048,7 +4048,7 @@ def hour(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.hour)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def minute(self) -> Series:
         """
@@ -4073,7 +4073,7 @@ def minute(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.minute)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def second(self) -> Series:
         """
@@ -4098,7 +4098,7 @@ def second(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.second)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def microsecond(self) -> Series:
         """
@@ -4130,7 +4130,7 @@ def microsecond(self) -> Series:
         ) * np.int32(1000)
         return self._return_result_like_self(micro + extra)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def nanosecond(self) -> Series:
         """
@@ -4155,7 +4155,7 @@ def nanosecond(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.nanosecond)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def weekday(self) -> Series:
         """
@@ -4192,7 +4192,7 @@ def weekday(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.weekday)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def dayofweek(self) -> Series:
         """
@@ -4239,7 +4239,7 @@ def dayofweek(self) -> Series:
 
     day_of_week = dayofweek
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def dayofyear(self) -> Series:
         """
@@ -4277,7 +4277,7 @@ def dayofyear(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.day_of_year)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def day_of_year(self) -> Series:
         """
@@ -4315,7 +4315,7 @@ def day_of_year(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.day_of_year)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_leap_year(self) -> Series:
         """
@@ -4371,7 +4371,7 @@ def is_leap_year(self) -> Series:
             self.series._column.is_leap_year.fillna(False)
         )
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def quarter(self) -> Series:
         """
@@ -4513,7 +4513,7 @@ def isocalendar(self) -> DataFrame:
             ca, index=self.series.index, attrs=self.series.attrs
         )
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_month_start(self) -> Series:
         """
@@ -4523,7 +4523,7 @@ def is_month_start(self) -> Series:
             self.series._column.is_month_start
         )
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def days_in_month(self) -> Series:
         """
@@ -4604,7 +4604,7 @@ def timetz(self):
     def unit(self) -> str:
         return self.series._column.time_unit
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_month_end(self) -> Series:
         """
@@ -4645,7 +4645,7 @@ def is_month_end(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.is_month_end)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_quarter_start(self) -> Series:
         """
@@ -4686,7 +4686,7 @@ def is_quarter_start(self) -> Series:
             self.series._column.is_quarter_start
         )
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_quarter_end(self) -> Series:
         """
@@ -4727,7 +4727,7 @@ def is_quarter_end(self) -> Series:
             self.series._column.is_quarter_end
         )
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_year_start(self) -> Series:
         """
@@ -4755,7 +4755,7 @@ def is_year_start(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.is_year_start)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_year_end(self) -> Series:
         """
@@ -5062,7 +5062,7 @@ class TimedeltaProperties(BaseDatelikeProperties):
     dtype: int64
     """
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def days(self) -> Series:
         """
@@ -5094,7 +5094,7 @@ def days(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.days)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def seconds(self) -> Series:
         """
@@ -5133,7 +5133,7 @@ def seconds(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.seconds)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def microseconds(self) -> Series:
         """
@@ -5165,7 +5165,7 @@ def microseconds(self) -> Series:
         """
         return self._return_result_like_self(self.series._column.microseconds)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def nanoseconds(self) -> Series:
         """
diff --git a/python/cudf/cudf/core/single_column_frame.py b/python/cudf/cudf/core/single_column_frame.py
index ad6b0ca1f01..7d79548aa8d 100644
--- a/python/cudf/cudf/core/single_column_frame.py
+++ b/python/cudf/cudf/core/single_column_frame.py
@@ -75,40 +75,40 @@ def _scan(
 
         return super()._scan(op, axis=axis, skipna=skipna, *args, **kwargs)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def name(self) -> Hashable:
         """Get the name of this object."""
         return next(iter(self._column_names))
 
-    @name.setter  # type: ignore
+    @name.setter
     @_performance_tracking
     def name(self, value: Hashable) -> None:
         self._data[value] = self._data.pop(self.name)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def ndim(self) -> int:
         """Number of dimensions of the underlying data, by definition 1."""
         return 1
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def shape(self) -> tuple[int]:
         """Get a tuple representing the dimensionality of the Index."""
         return (len(self),)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def _num_columns(self) -> int:
         return 1
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def _column(self) -> ColumnBase:
         return next(iter(self._columns))
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def values(self) -> cp.ndarray:
         col = self._column
@@ -158,7 +158,7 @@ def to_cupy(
             .reshape(len(self), order="F")
         )
 
-    @property  # type: ignore
+    @property  # type: ignore[explicit-override]
     @_performance_tracking
     def values_host(self) -> np.ndarray:
         return self._column.values_host
@@ -241,7 +241,7 @@ def _to_frame(self, name: Hashable, index: Index | None) -> DataFrame:
         # TODO: Avoid accessing DataFrame from the top level namespace
         return cudf.DataFrame._from_data(ca, index=index)
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_unique(self) -> bool:
         """Return boolean if values in the object are unique.
@@ -252,7 +252,7 @@ def is_unique(self) -> bool:
         """
         return self._column.is_unique
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_monotonic_increasing(self) -> bool:
         """Return boolean if values in the object are monotonically increasing.
@@ -263,7 +263,7 @@ def is_monotonic_increasing(self) -> bool:
         """
         return self._column.is_monotonic_increasing
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def is_monotonic_decreasing(self) -> bool:
         """Return boolean if values in the object are monotonically decreasing.
@@ -274,7 +274,7 @@ def is_monotonic_decreasing(self) -> bool:
         """
         return self._column.is_monotonic_decreasing
 
-    @property  # type: ignore
+    @property
     @_performance_tracking
     def __cuda_array_interface__(self) -> Mapping[str, Any]:
         # While the parent column class has a `__cuda_array_interface__` method
diff --git a/python/cudf/cudf/core/window/rolling.py b/python/cudf/cudf/core/window/rolling.py
index 8d260a6a114..c9413f68d3d 100644
--- a/python/cudf/cudf/core/window/rolling.py
+++ b/python/cudf/cudf/core/window/rolling.py
@@ -254,7 +254,7 @@ def __init__(
 
         if get_option("mode.pandas_compatible"):
             obj = obj.nans_to_nulls()
-        self.obj = obj  # type: ignore[assignment]
+        self.obj = obj
 
         self.window, self.min_periods = self._normalize_window_and_min_periods(
             window, min_periods
diff --git a/python/cudf/cudf/io/json.py b/python/cudf/cudf/io/json.py
index 6f9a5ca3528..ee37264c39e 100644
--- a/python/cudf/cudf/io/json.py
+++ b/python/cudf/cudf/io/json.py
@@ -221,7 +221,7 @@ def read_json(
             }
             df = DataFrame._from_data(data)
             # TODO: _add_df_col_struct_names expects dict but receives Mapping
-            ioutils._add_df_col_struct_names(df, res_child_names)  # type: ignore[arg-type]
+            ioutils._add_df_col_struct_names(df, res_child_names)
             return df
         else:
             table_w_meta = plc.io.json.read_json(
diff --git a/python/cudf/cudf/io/parquet.py b/python/cudf/cudf/io/parquet.py
index 6e366d13f33..fe13e5b8413 100644
--- a/python/cudf/cudf/io/parquet.py
+++ b/python/cudf/cudf/io/parquet.py
@@ -222,7 +222,7 @@ def _plc_write_parquet(
         )
     if metadata_file_path is not None:
         if is_list_like(metadata_file_path):
-            options.set_column_chunks_file_paths(metadata_file_path)  # type: ignore[arg-type]
+            options.set_column_chunks_file_paths(metadata_file_path)
         else:
             options.set_column_chunks_file_paths([metadata_file_path])
     if row_group_size_bytes is not None:
diff --git a/python/cudf/cudf/pandas/_wrappers/common.py b/python/cudf/cudf/pandas/_wrappers/common.py
index 163897d7c0c..7788df0e0f2 100644
--- a/python/cudf/cudf/pandas/_wrappers/common.py
+++ b/python/cudf/cudf/pandas/_wrappers/common.py
@@ -40,12 +40,12 @@ def arrow_array_method(self: _FastSlowProxy, *args, **kwargs):
         return pa.array(self._fsproxy_slow, *args, **kwargs)
 
 
-@property  # type: ignore
+@property  # type: ignore[misc]
 def cuda_array_interface(self: _FastSlowProxy):
     return self._fsproxy_fast.__cuda_array_interface__
 
 
-@property  # type: ignore
+@property  # type: ignore[misc]
 def array_interface(self: _FastSlowProxy):
     return self._fsproxy_slow.__array_interface__
 
@@ -59,5 +59,5 @@ def custom_iter(self: _FastSlowProxy):
     # falling back to GPU for iter method.
     return _maybe_wrap_result(
         iter(self._fsproxy_slow),
-        None,  # type: ignore
+        None,  # type: ignore[arg-type]
     )
diff --git a/python/cudf/cudf/pandas/_wrappers/pandas.py b/python/cudf/cudf/pandas/_wrappers/pandas.py
index 3e2c98a10da..d745910efbe 100644
--- a/python/cudf/cudf/pandas/_wrappers/pandas.py
+++ b/python/cudf/cudf/pandas/_wrappers/pandas.py
@@ -1338,8 +1338,8 @@ def _df_query_method(self, *args, local_dict=None, global_dict=None, **kwargs):
     )
 
 
-DataFrame.eval = _df_eval_method  # type: ignore
-DataFrame.query = _df_query_method  # type: ignore
+DataFrame.eval = _df_eval_method
+DataFrame.query = _df_query_method
 
 _JsonReader = make_intermediate_proxy_type(
     "_JsonReader",
diff --git a/python/cudf/cudf/pandas/annotation.py b/python/cudf/cudf/pandas/annotation.py
index a35fd96997b..9997c6a236b 100644
--- a/python/cudf/cudf/pandas/annotation.py
+++ b/python/cudf/cudf/pandas/annotation.py
@@ -7,7 +7,7 @@
     import nvtx
 except ImportError:
 
-    class nvtx:  # type: ignore
+    class nvtx:  # type: ignore[no-redef]
         """Noop-stub with the same API as nvtx."""
 
         push_range = lambda *args, **kwargs: None  # noqa: E731
diff --git a/python/cudf/cudf/pandas/fast_slow_proxy.py b/python/cudf/cudf/pandas/fast_slow_proxy.py
index 45cf672f228..c188c13e1f6 100644
--- a/python/cudf/cudf/pandas/fast_slow_proxy.py
+++ b/python/cudf/cudf/pandas/fast_slow_proxy.py
@@ -209,7 +209,7 @@ def as_gpu_object(self):
     def as_cpu_object(self):
         return self._fsproxy_fast_to_slow()
 
-    @property  # type: ignore
+    @property  # type: ignore[misc]
     def _fsproxy_state(self) -> _State:
         return (
             _State.FAST
@@ -253,7 +253,7 @@ def _fsproxy_state(self) -> _State:
 
     metaclass = _FastSlowProxyMeta
     if metaclasses:
-        metaclass = types.new_class(  # type: ignore
+        metaclass = types.new_class(  # type: ignore[assignment]
             f"{name}_Meta",
             (*metaclasses, _FastSlowProxyMeta),
             {},
@@ -312,7 +312,7 @@ def __init__(self, *args, **kwargs):
             f"Cannot directly instantiate object of type {type(self)}"
         )
 
-    @property  # type: ignore
+    @property  # type: ignore[misc]
     def _fsproxy_state(self):
         return (
             _State.FAST
@@ -715,7 +715,7 @@ class _CallableProxyMixin:
     """
 
     # For wrapped callables isinstance(self, FunctionType) should return True
-    __class__ = types.FunctionType  # type: ignore
+    __class__ = types.FunctionType  # type: ignore[assignment]
 
     def __call__(self, *args, **kwargs) -> Any:
         result, _ = _fast_slow_function_call(
@@ -840,7 +840,7 @@ def __get__(self, instance, owner) -> Any:
                 if instance is not None:
                     return _maybe_wrap_result(
                         getattr(instance._fsproxy_slow, self._name),
-                        None,  # type: ignore
+                        None,  # type: ignore[arg-type]
                     )
                 else:
                     raise e
@@ -874,7 +874,7 @@ def __get__(self, instance, owner) -> Any:
                 if self._private:
                     return _maybe_wrap_result(
                         getattr(instance._fsproxy_slow, self._name),
-                        None,  # type: ignore
+                        None,  # type: ignore[arg-type]
                     )
                 return _fast_slow_function_call(
                     getattr,
@@ -1387,7 +1387,7 @@ def is_proxy_instance(obj, type):
 }
 
 
-NUMPY_TYPES: set[type[np.generic]] = set(np.sctypeDict.values())  # type: ignore[arg-type]
+NUMPY_TYPES: set[type[np.generic]] = set(np.sctypeDict.values())
 
 
 _SPECIAL_METHODS: set[str] = {
diff --git a/python/cudf/cudf/pandas/module_accelerator.py b/python/cudf/cudf/pandas/module_accelerator.py
index 3087086f154..7213e5be961 100644
--- a/python/cudf/cudf/pandas/module_accelerator.py
+++ b/python/cudf/cudf/pandas/module_accelerator.py
@@ -547,7 +547,7 @@ def getattr_real_or_wrapped(
             # disabled when the child was launched. That is a fairly rare pattern though
             # and we can document the limitations.
             # The main thread is always started, so the ident is always an int
-            or loader._disable_count[threading.main_thread().ident] > 0  # type: ignore
+            or loader._disable_count[threading.main_thread().ident] > 0  # type: ignore[index]
         )
         if not use_real:
             # Only need to check the denylist if we're not turned off.
diff --git a/python/cudf/cudf/pandas/scripts/conftest-patch.py b/python/cudf/cudf/pandas/scripts/conftest-patch.py
index 8fdf321c2a2..56c29a144a4 100644
--- a/python/cudf/cudf/pandas/scripts/conftest-patch.py
+++ b/python/cudf/cudf/pandas/scripts/conftest-patch.py
@@ -32,14 +32,14 @@ def null_assert_warnings(*args, **kwargs):
         pass
 
 
-@pytest.fixture(scope="session", autouse=True)  # type: ignore
+@pytest.fixture(scope="session", autouse=True)
 def patch_testing_functions():
     tm.assert_produces_warning = null_assert_warnings  # noqa: F821
     pytest.raises = replace_kwargs({"match": None})(pytest.raises)
 
 
 # Dictionary to store function call counts
-function_call_counts = defaultdict(lambda: defaultdict(int))  # type: ignore
+function_call_counts = defaultdict(lambda: defaultdict(int))  # type: ignore[var-annotated]
 
 # The specific functions to track
 FUNCTION_NAME = {"_slow_function_call", "_fast_function_call"}
diff --git a/python/cudf_polars/cudf_polars/containers/datatype.py b/python/cudf_polars/cudf_polars/containers/datatype.py
index 8290efccbf9..e2a1cfcd911 100644
--- a/python/cudf_polars/cudf_polars/containers/datatype.py
+++ b/python/cudf_polars/cudf_polars/containers/datatype.py
@@ -119,9 +119,9 @@ def children(self) -> list[DataType]:
         # these type ignores are needed because the type checker doesn't
         # see that these equality checks passing imply a specific type for each child field.
         if self.plc_type.id() == plc.TypeId.STRUCT:
-            return [DataType(field.dtype) for field in self.polars_type.fields]  # type: ignore[attr-defined]
+            return [DataType(field.dtype) for field in self.polars_type.fields]
         elif self.plc_type.id() == plc.TypeId.LIST:
-            return [DataType(self.polars_type.inner)]  # type: ignore[attr-defined]
+            return [DataType(self.polars_type.inner)]
         return []
 
     def scale(self) -> int:
diff --git a/python/cudf_polars/cudf_polars/dsl/expressions/string.py b/python/cudf_polars/cudf_polars/dsl/expressions/string.py
index b23fb132217..a40afc644ee 100644
--- a/python/cudf_polars/cudf_polars/dsl/expressions/string.py
+++ b/python/cudf_polars/cudf_polars/dsl/expressions/string.py
@@ -42,9 +42,9 @@ def _dtypes_for_json_decode(dtype: DataType) -> JsonDecodeType:
         return [
             (field.name, child.plc_type, _dtypes_for_json_decode(child))
             for field, child in zip(
-                dtype.polars_type.fields,  # type: ignore[attr-defined]
+                dtype.polars_type.fields,
                 dtype.children,
-                strict=True,  # type: ignore[attr-defined]
+                strict=True,
             )
         ]
     else:
@@ -853,13 +853,13 @@ def do_evaluate(
                 # TODO: Maybe accept a string scalar in
                 # cudf::strings::pad to avoid DtoH transfer
                 # See https://github.com/rapidsai/cudf/issues/20202 for we type ignore
-                width: int = width_col.obj.to_scalar().to_py()  # type: ignore[assignment, no-redef]
+                width: int = width_col.obj.to_scalar().to_py()  # type: ignore[no-redef]
             return Column(
                 plc.strings.padding.pad(
                     column.obj,
                     width,  # type: ignore[arg-type]
                     plc.strings.SideType.LEFT,
-                    char,  # type: ignore[arg-type]
+                    char,
                 ),
                 dtype=self.dtype,
             )
@@ -872,13 +872,13 @@ def do_evaluate(
                 (char,) = self.options
                 # TODO: Maybe accept a string scalar in
                 # cudf::strings::pad to avoid DtoH transfer
-                width: int = width_col.obj.to_scalar().to_py()  # type: ignore[assignment, no-redef]
+                width: int = width_col.obj.to_scalar().to_py()  # type: ignore[no-redef]
             return Column(
                 plc.strings.padding.pad(
                     column.obj,
                     width,  # type: ignore[arg-type]
                     plc.strings.SideType.RIGHT,
-                    char,  # type: ignore[arg-type]
+                    char,
                 ),
                 dtype=self.dtype,
             )
diff --git a/python/cudf_polars/cudf_polars/dsl/expressions/struct.py b/python/cudf_polars/cudf_polars/dsl/expressions/struct.py
index 5d3ff47da97..b9749a1bbba 100644
--- a/python/cudf_polars/cudf_polars/dsl/expressions/struct.py
+++ b/python/cudf_polars/cudf_polars/dsl/expressions/struct.py
@@ -93,7 +93,7 @@ def do_evaluate(
             field_index = next(
                 (
                     i
-                    for i, field in enumerate(self.children[0].dtype.polars_type.fields)  # type: ignore[attr-defined]
+                    for i, field in enumerate(self.children[0].dtype.polars_type.fields)
                     if field.name == self.options[0]
                 ),
                 None,
@@ -113,7 +113,7 @@ def do_evaluate(
                 table,
                 [
                     (field.name, [])
-                    for field in self.children[0].dtype.polars_type.fields  # type: ignore[attr-defined]
+                    for field in self.children[0].dtype.polars_type.fields
                 ],
             )
             options = (
diff --git a/python/cudf_polars/cudf_polars/dsl/to_ast.py b/python/cudf_polars/cudf_polars/dsl/to_ast.py
index 2e053a34f8b..320868a6c25 100644
--- a/python/cudf_polars/cudf_polars/dsl/to_ast.py
+++ b/python/cudf_polars/cudf_polars/dsl/to_ast.py
@@ -224,7 +224,7 @@ def _(node: expr.BooleanFunction, self: Transformer) -> plc_expr.Expression:
                 #
                 # the type-ignore is safe because the for plc.TypeID.LIST, we know
                 # we have a polars.List type, which has an inner attribute.
-                plc_dtype = DataType(haystack.dtype.polars_type.inner).plc_type  # type: ignore[attr-defined]
+                plc_dtype = DataType(haystack.dtype.polars_type.inner).plc_type
             else:
                 plc_dtype = haystack.dtype.plc_type  # pragma: no cover
             values = (
diff --git a/python/cudf_polars/cudf_polars/experimental/benchmarks/pdsds.py b/python/cudf_polars/cudf_polars/experimental/benchmarks/pdsds.py
index 6041d9a9d79..88dbca113e7 100644
--- a/python/cudf_polars/cudf_polars/experimental/benchmarks/pdsds.py
+++ b/python/cudf_polars/cudf_polars/experimental/benchmarks/pdsds.py
@@ -58,7 +58,7 @@ def valid_query(name: str) -> bool:
 class PDSDSQueriesMeta(type):
     """Metaclass used for query lookup."""
 
-    def __getattr__(cls, name: str):  # type: ignore
+    def __getattr__(cls, name: str):  # type: ignore[no-untyped-def]
         """Query lookup."""
         if valid_query(name):
             q_num = int(name[1:])
diff --git a/python/cudf_polars/cudf_polars/experimental/benchmarks/utils.py b/python/cudf_polars/cudf_polars/experimental/benchmarks/utils.py
index 68f06e105b8..c7b304c01c9 100644
--- a/python/cudf_polars/cudf_polars/experimental/benchmarks/utils.py
+++ b/python/cudf_polars/cudf_polars/experimental/benchmarks/utils.py
@@ -468,7 +468,7 @@ def print_query_plan(
         )
 
 
-def initialize_dask_cluster(run_config: RunConfig, args: argparse.Namespace):  # type: ignore
+def initialize_dask_cluster(run_config: RunConfig, args: argparse.Namespace):  # type: ignore[no-untyped-def]
     """Initialize a Dask distributed cluster."""
     if run_config.cluster != "distributed":
         return None
@@ -849,7 +849,7 @@ def run_polars(
     validation_failures: list[int] = []
     query_failures: list[tuple[int, int]] = []
 
-    client = initialize_dask_cluster(run_config, args)  # type: ignore
+    client = initialize_dask_cluster(run_config, args)
 
     records: defaultdict[int, list[Record]] = defaultdict(list)
     engine: pl.GPUEngine | None = None
@@ -892,8 +892,8 @@ def run_polars(
                     gather_shuffle_statistics,
                 )
 
-                shuffle_stats = gather_shuffle_statistics(client)  # type: ignore[arg-type]
-                clear_shuffle_statistics(client)  # type: ignore[arg-type]
+                shuffle_stats = gather_shuffle_statistics(client)
+                clear_shuffle_statistics(client)
             else:
                 shuffle_stats = None
 
diff --git a/python/cudf_polars/cudf_polars/testing/asserts.py b/python/cudf_polars/cudf_polars/testing/asserts.py
index 7b1497e6880..0db810cd0d6 100644
--- a/python/cudf_polars/cudf_polars/testing/asserts.py
+++ b/python/cudf_polars/cudf_polars/testing/asserts.py
@@ -111,8 +111,8 @@ def assert_gpu_result_equal(
 
     # These keywords are correct, but mypy doesn't see that.
     # the 'misc' is for 'error: Keywords must be strings'
-    expect = lazydf.collect(**final_polars_collect_kwargs)  # type: ignore[call-overload,misc]
-    got = lazydf.collect(**final_cudf_collect_kwargs, engine=engine)  # type: ignore[call-overload,misc]
+    expect = lazydf.collect(**final_polars_collect_kwargs)
+    got = lazydf.collect(**final_cudf_collect_kwargs, engine=engine)
 
     assert_kwargs_bool: dict[str, bool] = {
         "check_row_order": check_row_order,
@@ -135,7 +135,7 @@ def assert_gpu_result_equal(
         expect,
         got,
         **assert_kwargs_bool,
-        **tol_kwargs,  # type: ignore[arg-type]
+        **tol_kwargs,
     )
 
 
@@ -292,7 +292,7 @@ def assert_collect_raises(
     )
 
     try:
-        lazydf.collect(**final_polars_collect_kwargs)  # type: ignore[call-overload,misc]
+        lazydf.collect(**final_polars_collect_kwargs)
     except polars_except:
         pass
     except Exception as e:
@@ -305,7 +305,7 @@ def assert_collect_raises(
 
     engine = GPUEngine(raise_on_fail=True)
     try:
-        lazydf.collect(**final_cudf_collect_kwargs, engine=engine)  # type: ignore[call-overload,misc]
+        lazydf.collect(**final_cudf_collect_kwargs, engine=engine)
     except cudf_except:
         pass
     except Exception as e:
diff --git a/python/cudf_polars/cudf_polars/testing/plugin.py b/python/cudf_polars/cudf_polars/testing/plugin.py
index 619901821d8..d8094d0e129 100644
--- a/python/cudf_polars/cudf_polars/testing/plugin.py
+++ b/python/cudf_polars/cudf_polars/testing/plugin.py
@@ -57,11 +57,11 @@ def pytest_configure(config: pytest.Config) -> None:
         collect = polars.LazyFrame.collect
         engine = polars.GPUEngine(raise_on_fail=no_fallback)
         # https://github.com/python/mypy/issues/2427
-        polars.LazyFrame.collect = partialmethod(collect, engine=engine)  # type: ignore[method-assign,assignment]
+        polars.LazyFrame.collect = partialmethod(collect, engine=engine)
     elif executor == "in-memory":
         collect = polars.LazyFrame.collect
         engine = polars.GPUEngine(executor=executor)
-        polars.LazyFrame.collect = partialmethod(collect, engine=engine)  # type: ignore[method-assign,assignment]
+        polars.LazyFrame.collect = partialmethod(collect, engine=engine)
     elif executor == "streaming" and blocksize_mode == "small":
         executor_options: dict[str, Any] = {}
         executor_options["max_rows_per_partition"] = 4
@@ -70,7 +70,7 @@ def pytest_configure(config: pytest.Config) -> None:
         executor_options["fallback_mode"] = StreamingFallbackMode.SILENT
         collect = polars.LazyFrame.collect
         engine = polars.GPUEngine(executor=executor, executor_options=executor_options)
-        polars.LazyFrame.collect = partialmethod(collect, engine=engine)  # type: ignore[method-assign,assignment]
+        polars.LazyFrame.collect = partialmethod(collect, engine=engine)
     else:
         # run with streaming executor and default blocksize
         polars.Config.set_engine_affinity("gpu")
diff --git a/python/cudf_polars/tests/dsl/test_traversal.py b/python/cudf_polars/tests/dsl/test_traversal.py
index a3cae36c845..05f2a07c2fc 100644
--- a/python/cudf_polars/tests/dsl/test_traversal.py
+++ b/python/cudf_polars/tests/dsl/test_traversal.py
@@ -237,7 +237,7 @@ def _transform(e: expr.Expr, fn: ExprTransformer) -> expr.Expr:
     @_transform.register
     def _(e: expr.Col, fn: ExprTransformer):
         # We've added an extra key to the state, so ignore this type error.
-        mapping = fn.state["mapping"]  # type: ignore
+        mapping = fn.state["mapping"]  # type: ignore[typeddict-item]
         if e.name in mapping:
             return type(e)(e.dtype, mapping[e.name])
         return e
diff --git a/python/cudf_polars/tests/experimental/test_shuffle.py b/python/cudf_polars/tests/experimental/test_shuffle.py
index 014b6c7582b..90565b0be3d 100644
--- a/python/cudf_polars/tests/experimental/test_shuffle.py
+++ b/python/cudf_polars/tests/experimental/test_shuffle.py
@@ -72,5 +72,5 @@ def test_hash_shuffle(df: pl.LazyFrame, engine: pl.GPUEngine) -> None:
     result = evaluate_streaming(qir3, options, context=IRExecutionContext()).to_polars()
     # ignore is for polars' EngineType, which isn't publicly exported.
     # https://github.com/pola-rs/polars/issues/17420
-    expect = df.collect(engine="cpu")  # type: ignore[call-overload]
+    expect = df.collect(engine="cpu")
     assert_frame_equal(result, expect, check_row_order=False)
diff --git a/python/cudf_polars/tests/test_config.py b/python/cudf_polars/tests/test_config.py
index 6d8befef718..16d0097450e 100644
--- a/python/cudf_polars/tests/test_config.py
+++ b/python/cudf_polars/tests/test_config.py
@@ -490,7 +490,7 @@ def test_validate_parquet_options(option: str) -> None:
 def test_validate_raise_on_fail() -> None:
     with pytest.raises(TypeError, match="'raise_on_fail' must be"):
         ConfigOptions.from_polars_engine(
-            pl.GPUEngine(executor="streaming", raise_on_fail=object())  # type: ignore[arg-type]
+            pl.GPUEngine(executor="streaming", raise_on_fail=object())
         )
 
 
diff --git a/python/cudf_polars/tests/test_window_functions.py b/python/cudf_polars/tests/test_window_functions.py
index 284dec13ffb..66cedb13488 100644
--- a/python/cudf_polars/tests/test_window_functions.py
+++ b/python/cudf_polars/tests/test_window_functions.py
@@ -106,7 +106,7 @@ def test_over_mapping_strategy(df: pl.LazyFrame, mapping_strategy: str):
     # ignore is for polars' WindowMappingStrategy, which isn't publicly exported.
     # https://github.com/pola-rs/polars/issues/17420
     q = df.with_columns(
-        [pl.col("b").rank().over(pl.col("a"), mapping_strategy=mapping_strategy)]  # type: ignore[arg-type]
+        [pl.col("b").rank().over(pl.col("a"), mapping_strategy=mapping_strategy)]
     )
     if not POLARS_VERSION_LT_132 and mapping_strategy == "group_to_rows":
         assert_gpu_result_equal(q)
@@ -143,6 +143,6 @@ def test_rolling_closed(df: pl.LazyFrame, closed: str):
     # ignore is for polars' ClosedInterval, which isn't publicly exported.
     # https://github.com/pola-rs/polars/issues/17420
     query = df.with_columns(
-        [pl.col("b").sum().rolling(period="2d", index_column="date", closed=closed)]  # type: ignore[arg-type]
+        [pl.col("b").sum().rolling(period="2d", index_column="date", closed=closed)]
     )
     assert_gpu_result_equal(query)