BUG: raise TypeError when array not like 1D in pandas.array

doc/source/whatsnew/v3.0.0.rst

@@ -1378,7 +1378,8 @@ Other
 ^^^^^
 - Bug in :class:`DataFrame` when passing a ``dict`` with a NA scalar and ``columns`` that would always return ``np.nan`` (:issue:`57205`)
 - Bug in :class:`Series` ignoring errors when trying to convert :class:`Series` input data to the given ``dtype`` (:issue:`60728`)
-- Bug in :func:`eval` on :class:`.ExtensionArray` on including division ``/`` failed with a ``TypeError``. (:issue:`58748`)
+- Bug in :func:`array` where it did not always raise an error when the passed data was not like 1D. (:issue:`63112`)
+- Bug in :func:`eval` on :class:`ExtensionArray` on including division ``/`` failed with a ``TypeError``. (:issue:`58748`)
 - Bug in :func:`eval` where method calls on binary operations like ``(x + y).dropna()`` would raise ``AttributeError: 'BinOp' object has no attribute 'value'`` (:issue:`61175`)
 - Bug in :func:`eval` where the names of the :class:`Series` were not preserved when using ``engine="numexpr"``. (:issue:`10239`)
 - Bug in :func:`eval` with ``engine="numexpr"`` returning unexpected result for float division. (:issue:`59736`)

pandas/_libs/lib.pyi

@@ -165,6 +165,7 @@ def maybe_indices_to_slice(
     indices: npt.NDArray[np.intp],
     max_len: int,
 ) -> slice | npt.NDArray[np.intp]: ...
+def is_all_scalar(obj: list | tuple) -> bool: ...
 def is_all_arraylike(obj: list) -> bool: ...
 
 # -----------------------------------------------------------------

pandas/_libs/lib.pyx

@@ -861,6 +861,24 @@ cpdef ndarray[object] ensure_string_array(
     return result
 
 
+def is_all_scalar(obj: list | tuple) -> bool:
+    cdef:
+        Py_ssize_t i, n = len(obj)
+        object temp
+
+    all_scalars = True
+
+    for i in range(n):
+        temp = obj[i]
+        if isinstance(temp, (bytes, str)):
+            continue
+        elif hasattr(temp, "__iter__"):
+            all_scalars = False
+            break
+
+    return all_scalars
+
+
 def is_all_arraylike(obj: list) -> bool:
     """
     Should we treat these as levels of a MultiIndex, as opposed to Index items?

pandas/core/construction.py

@@ -321,6 +321,11 @@ def array(
             return data.copy()
         return data
 
+    # to avoid returning an array of string representation of objects.
+    if isinstance(dtype, StringDtype) and isinstance(data, (list, tuple)):
+        if not lib.is_all_scalar(data):
+            raise TypeError("Values must be a 1D list-like")
+
     if isinstance(dtype, ExtensionDtype):
         cls = dtype.construct_array_type()
         return cls._from_sequence(data, dtype=dtype, copy=copy)

pandas/tests/arrays/test_array.py

@@ -460,6 +460,26 @@ def test_nd_raises(data):
         pd.array(data, dtype="int64")
 
 
+@pytest.mark.parametrize(
+    "data",
+    [
+        # string 2D
+        [["a"], ["b"]],
+        # int 2D
+        [[1], [2]],
+        # float 2D
+        [[1.0], [2.0]],
+        # mixed 2D
+        [[1, 2], ["a", "b"]],
+        # mixed 3D
+        [[[1]], [["a"]], [[3.14]]],
+    ],
+)
+def test_not_1D_like_raises(data):
+    with pytest.raises(TypeError, match="Values must be a 1D list-like"):
+        pd.array(data, dtype=pd.StringDtype())
+
+
 def test_scalar_raises():
     with pytest.raises(ValueError, match="Cannot pass scalar '1'"):
         pd.array(1)