handling macos13 platform specific error

Author: Koookadooo

pandas/core/dtypes/dtypes.py

@@ -2274,32 +2274,30 @@ def name(self) -> str:  # type: ignore[override]
 
     @cache_readonly
     def numpy_dtype(self) -> np.dtype:
-    """Return an instance of the related numpy dtype."""
-    if pa.types.is_timestamp(self.pyarrow_dtype):
-        if self.pyarrow_dtype.tz is not None:
+        """Return an instance of the related numpy dtype."""
+        if pa.types.is_timestamp(self.pyarrow_dtype):
+            if self.pyarrow_dtype.tz is not None:
+                return np.dtype(f"datetime64[{self.pyarrow_dtype.unit}]")
             return np.dtype(f"datetime64[{self.pyarrow_dtype.unit}]")
-        return np.dtype(f"datetime64[{self.pyarrow_dtype.unit}]")
-    if pa.types.is_duration(self.pyarrow_dtype):
-        return np.dtype(f"timedelta64[{self.pyarrow_dtype.unit}]")
-    if pa.types.is_string(self.pyarrow_dtype) or pa.types.is_large_string(
-        self.pyarrow_dtype
-    ):
-        return np.dtype(str)
-    try:
-        np_dtype = self.pyarrow_dtype.to_pandas_dtype()
-        
-        if isinstance(np_dtype, object):
-            if hasattr(np_dtype, "categories") and isinstance(np_dtype.categories, pd.IntervalIndex):
-                return np.dtype(object)
-        
-        if isinstance(np_dtype, DatetimeTZDtype):
-            return np.dtype(f"datetime64[{np_dtype.unit}]")
-        
-        return np.dtype(np_dtype)
-    except (NotImplementedError, TypeError):
-        return np.dtype(object)
-
-
+        if pa.types.is_duration(self.pyarrow_dtype):
+            return np.dtype(f"timedelta64[{self.pyarrow_dtype.unit}]")
+        if pa.types.is_string(self.pyarrow_dtype) or pa.types.is_large_string(
+            self.pyarrow_dtype
+        ):
+            return np.dtype(str)
+        try:
+            np_dtype = self.pyarrow_dtype.to_pandas_dtype()
+            
+            if isinstance(np_dtype, object):
+                if hasattr(np_dtype, "categories") and isinstance(np_dtype.categories, pd.IntervalIndex):
+                    return np.dtype(object)
+            
+            if isinstance(np_dtype, DatetimeTZDtype):
+                return np.dtype(f"datetime64[{np_dtype.unit}]")
+            
+            return np.dtype(np_dtype)
+        except (NotImplementedError, TypeError):
+            return np.dtype(object)
 
     @cache_readonly
     def kind(self) -> str: