add conditional for checking ndim

Author: antareepsarkar

pandas/core/arrays/numpy_.py

@@ -118,8 +118,7 @@ def __init__(
                 f"'values' must be a NumPy array, not {type(values).__name__}"
             )
 
-        if values.ndim == 0:
-            # Technically we support 2, but do not advertise that fact.
+        if values.ndim != 1:
             raise ValueError("NumpyExtensionArray must be 1-dimensional.")
 
         if copy:

pandas/core/construction.py

@@ -360,8 +360,6 @@ def array(
             # StringArray/ArrowStringArray depending on pd.options.mode.string_storage
             dtype = StringDtype()
             cls = dtype.construct_array_type()
-            if data.ndim != 1:
-                raise ValueError("NumpyExtensionArray must be 1-dimensional")
             return cls._from_sequence(data, dtype=dtype, copy=copy)
 
         elif data.dtype.kind in "iu":

pandas/tests/arrays/test_array.py

@@ -451,7 +451,13 @@ def test_array_inference_fails(data):
     tm.assert_extension_array_equal(result, expected)
 
 
-@pytest.mark.parametrize("data,dtype", [(np.array(0),"int64"),(np.array([[1, 2], ["a", "b"]]),object)])
+@pytest.mark.parametrize(
+    "data,dtype",
+    [
+        (np.array(0), "int64"),
+        (np.array([[1, 2], ["a", "b"]]), object),
+    ],
+)
 def test_nd_raises(data, dtype):
     with pytest.raises(ValueError, match="NumpyExtensionArray must be 1-dimensional"):
         pd.array(data, dtype=dtype)