diff --git a/pandas/core/arrays/floating.py b/pandas/core/arrays/floating.py
index 4aed39d7edb92..fe3a7ae3c8631 100644
--- a/pandas/core/arrays/floating.py
+++ b/pandas/core/arrays/floating.py
@@ -386,9 +386,9 @@ def astype(self, dtype, copy: bool = True) -> ArrayLike:
         # coerce
         if is_float_dtype(dtype):
             # In astype, we consider dtype=float to also mean na_value=np.nan
-            kwargs = dict(na_value=np.nan)
+            kwargs = {"na_value": np.nan}
         elif is_datetime64_dtype(dtype):
-            kwargs = dict(na_value=np.datetime64("NaT"))
+            kwargs = {"na_value": np.datetime64("NaT")}
         else:
             kwargs = {}
 
diff --git a/pandas/core/arrays/numpy_.py b/pandas/core/arrays/numpy_.py
index 4eb67dcd12728..50d12703c3a30 100644
--- a/pandas/core/arrays/numpy_.py
+++ b/pandas/core/arrays/numpy_.py
@@ -273,12 +273,12 @@ def _values_for_factorize(self) -> Tuple[np.ndarray, int]:
     # Reductions
 
     def any(self, *, axis=None, out=None, keepdims=False, skipna=True):
-        nv.validate_any((), dict(out=out, keepdims=keepdims))
+        nv.validate_any((), {"out": out, "keepdims": keepdims})
         result = nanops.nanany(self._ndarray, axis=axis, skipna=skipna)
         return self._wrap_reduction_result(axis, result)
 
     def all(self, *, axis=None, out=None, keepdims=False, skipna=True):
-        nv.validate_all((), dict(out=out, keepdims=keepdims))
+        nv.validate_all((), {"out": out, "keepdims": keepdims})
         result = nanops.nanall(self._ndarray, axis=axis, skipna=skipna)
         return self._wrap_reduction_result(axis, result)
 
@@ -311,7 +311,7 @@ def prod(self, *, axis=None, skipna=True, min_count=0, **kwargs) -> Scalar:
         return self._wrap_reduction_result(axis, result)
 
     def mean(self, *, axis=None, dtype=None, out=None, keepdims=False, skipna=True):
-        nv.validate_mean((), dict(dtype=dtype, out=out, keepdims=keepdims))
+        nv.validate_mean((), {"dtype": dtype, "out": out, "keepdims": keepdims})
         result = nanops.nanmean(self._ndarray, axis=axis, skipna=skipna)
         return self._wrap_reduction_result(axis, result)
 
@@ -319,7 +319,7 @@ def median(
         self, *, axis=None, out=None, overwrite_input=False, keepdims=False, skipna=True
     ):
         nv.validate_median(
-            (), dict(out=out, overwrite_input=overwrite_input, keepdims=keepdims)
+            (), {"out": out, "overwrite_input": overwrite_input, "keepdims": keepdims}
         )
         result = nanops.nanmedian(self._ndarray, axis=axis, skipna=skipna)
         return self._wrap_reduction_result(axis, result)
@@ -328,7 +328,7 @@ def std(
         self, *, axis=None, dtype=None, out=None, ddof=1, keepdims=False, skipna=True
     ):
         nv.validate_stat_ddof_func(
-            (), dict(dtype=dtype, out=out, keepdims=keepdims), fname="std"
+            (), {"dtype": dtype, "out": out, "keepdims": keepdims}, fname="std"
         )
         result = nanops.nanstd(self._ndarray, axis=axis, skipna=skipna, ddof=ddof)
         return self._wrap_reduction_result(axis, result)
@@ -337,7 +337,7 @@ def var(
         self, *, axis=None, dtype=None, out=None, ddof=1, keepdims=False, skipna=True
     ):
         nv.validate_stat_ddof_func(
-            (), dict(dtype=dtype, out=out, keepdims=keepdims), fname="var"
+            (), {"dtype": dtype, "out": out, "keepdims": keepdims}, fname="var"
         )
         result = nanops.nanvar(self._ndarray, axis=axis, skipna=skipna, ddof=ddof)
         return self._wrap_reduction_result(axis, result)
@@ -346,21 +346,21 @@ def sem(
         self, *, axis=None, dtype=None, out=None, ddof=1, keepdims=False, skipna=True
     ):
         nv.validate_stat_ddof_func(
-            (), dict(dtype=dtype, out=out, keepdims=keepdims), fname="sem"
+            (), {"dtype": dtype, "out": out, "keepdims": keepdims}, fname="sem"
         )
         result = nanops.nansem(self._ndarray, axis=axis, skipna=skipna, ddof=ddof)
         return self._wrap_reduction_result(axis, result)
 
     def kurt(self, *, axis=None, dtype=None, out=None, keepdims=False, skipna=True):
         nv.validate_stat_ddof_func(
-            (), dict(dtype=dtype, out=out, keepdims=keepdims), fname="kurt"
+            (), {"dtype": dtype, "out": out, "keepdims": keepdims}, fname="kurt"
         )
         result = nanops.nankurt(self._ndarray, axis=axis, skipna=skipna)
         return self._wrap_reduction_result(axis, result)
 
     def skew(self, *, axis=None, dtype=None, out=None, keepdims=False, skipna=True):
         nv.validate_stat_ddof_func(
-            (), dict(dtype=dtype, out=out, keepdims=keepdims), fname="skew"
+            (), {"dtype": dtype, "out": out, "keepdims": keepdims}, fname="skew"
         )
         result = nanops.nanskew(self._ndarray, axis=axis, skipna=skipna)
         return self._wrap_reduction_result(axis, result)