diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 74f90ce9eea..36cc76cbf8d 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -9141,7 +9141,7 @@ def polyfit(
lhs = np.vander(x, order)
if rcond is None:
- rcond = x.shape[0] * np.finfo(x.dtype).eps # type: ignore[assignment]
+ rcond = x.shape[0] * np.finfo(x.dtype).eps
# Weights:
if w is not None:
diff --git a/xarray/core/dtypes.py b/xarray/core/dtypes.py
index 362cd78c689..96f660039b5 100644
--- a/xarray/core/dtypes.py
+++ b/xarray/core/dtypes.py
@@ -62,7 +62,7 @@ def maybe_promote(dtype: np.dtype) -> tuple[np.dtype, Any]:
# N.B. these casting rules should match pandas
dtype_: np.typing.DTypeLike
fill_value: Any
- if HAS_STRING_DTYPE and np.issubdtype(dtype, np.dtypes.StringDType()): # type: ignore[attr-defined]
+ if HAS_STRING_DTYPE and np.issubdtype(dtype, np.dtypes.StringDType()):
# for now, we always promote string dtypes to object for consistency with existing behavior
# TODO: refactor this once we have a better way to handle numpy vlen-string dtypes
dtype_ = object
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