BUG: validate Index data is 1D + deprecate multi-dim indexing

pandas/core/indexes/base.py

@@ -442,6 +442,9 @@ def __new__(
                             pass
             if kwargs:
                 raise TypeError(f"Unexpected keyword arguments {repr(set(kwargs))}")
+            if subarr.ndim > 1:
+                # GH#13601, GH#20285, GH#27125
+                raise ValueError("Index data must be 1-dimensional")
             return cls._simple_new(subarr, name, **kwargs)
 
         elif hasattr(data, "__array__"):
@@ -657,7 +660,7 @@ def __array_wrap__(self, result, context=None):
         Gets called after a ufunc.
         """
         result = lib.item_from_zerodim(result)
-        if is_bool_dtype(result) or lib.is_scalar(result):
+        if is_bool_dtype(result) or lib.is_scalar(result) or np.ndim(result) > 1:
             return result
 
         attrs = self._get_attributes_dict()
@@ -736,11 +739,10 @@ def astype(self, dtype, copy=True):
             return Index(np.asarray(self), dtype=dtype, copy=copy)
 
         try:
-            return Index(
-                self.values.astype(dtype, copy=copy), name=self.name, dtype=dtype
-            )
+            casted = self.values.astype(dtype, copy=copy)
         except (TypeError, ValueError):
             raise TypeError(f"Cannot cast {type(self).__name__} to dtype {dtype}")
+        return Index(casted, name=self.name, dtype=dtype)
 
     _index_shared_docs[
         "take"
@@ -4024,6 +4026,10 @@ def __getitem__(self, key):
         key = com.values_from_object(key)
         result = getitem(key)
         if not is_scalar(result):
+            if np.ndim(result) > 1:
+                # GH#27125 indexer like idx[:, None] expands dim, but we
+                #  cannot do that and keep an index, so return ndarray
+                return result
             return promote(result)
         else:
             return result

pandas/core/indexes/numeric.py

@@ -73,6 +73,10 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None):
         else:
             subarr = data
 
+        if subarr.ndim > 1:
+            # GH#13601, GH#20285, GH#27125
+            raise ValueError("Index data must be 1-dimensional")
+
         name = maybe_extract_name(name, data, cls)
         return cls._simple_new(subarr, name=name)
 

pandas/tests/indexes/test_base.py

@@ -2782,9 +2782,33 @@ def test_shape_of_invalid_index():
     # about this). However, as long as this is not solved in general,this test ensures
     # that the returned shape is consistent with this underlying array for
     # compat with matplotlib (see https://github.com/pandas-dev/pandas/issues/27775)
-    a = np.arange(8).reshape(2, 2, 2)
-    idx = pd.Index(a)
-    assert idx.shape == a.shape
-
     idx = pd.Index([0, 1, 2, 3])
     assert idx[:, None].shape == (4, 1)
+
+
+def test_validate_1d_input():
+    # GH#27125 check that we do not have >1-dimensional input
+    msg = "Index data must be 1-dimensional"
+
+    arr = np.arange(8).reshape(2, 2, 2)
+    with pytest.raises(ValueError, match=msg):
+        pd.Index(arr)
+
+    with pytest.raises(ValueError, match=msg):
+        pd.Float64Index(arr.astype(np.float64))
+
+    with pytest.raises(ValueError, match=msg):
+        pd.Int64Index(arr.astype(np.int64))
+
+    with pytest.raises(ValueError, match=msg):
+        pd.UInt64Index(arr.astype(np.uint64))
+
+    df = pd.DataFrame(arr.reshape(4, 2))
+    with pytest.raises(ValueError, match=msg):
+        pd.Index(df)
+
+    # GH#13601 trying to assign a multi-dimensional array to an index is not
+    #  allowed
+    ser = pd.Series(0, range(4))
+    with pytest.raises(ValueError, match=msg):
+        ser.index = np.array([[2, 3]] * 4)

pandas/tests/indexing/test_indexing.py

@@ -83,12 +83,9 @@ def test_getitem_ndarray_3d(self, index, obj, idxr, idxr_id):
         msg = (
             r"Buffer has wrong number of dimensions \(expected 1,"
             r" got 3\)|"
-            "The truth value of an array with more than one element is"
-            " ambiguous|"
             "Cannot index with multidimensional key|"
             r"Wrong number of dimensions. values.ndim != ndim \[3 != 1\]|"
-            "No matching signature found|"  # TypeError
-            "unhashable type: 'numpy.ndarray'"  # TypeError
+            "Index data must be 1-dimensional"
         )
 
         if (
@@ -106,18 +103,7 @@ def test_getitem_ndarray_3d(self, index, obj, idxr, idxr_id):
         ):
             idxr[nd3]
         else:
-            if (
-                isinstance(obj, DataFrame)
-                and idxr_id == "getitem"
-                and index.inferred_type == "boolean"
-            ):
-                error = TypeError
-            elif idxr_id == "getitem" and index.inferred_type == "interval":
-                error = TypeError
-            else:
-                error = ValueError
-
-            with pytest.raises(error, match=msg):
+            with pytest.raises(ValueError, match=msg):
                 idxr[nd3]
 
     @pytest.mark.parametrize(
@@ -148,14 +134,12 @@ def test_setitem_ndarray_3d(self, index, obj, idxr, idxr_id):
         msg = (
             r"Buffer has wrong number of dimensions \(expected 1,"
             r" got 3\)|"
-            "The truth value of an array with more than one element is"
-            " ambiguous|"
-            "Only 1-dimensional input arrays are supported|"
             "'pandas._libs.interval.IntervalTree' object has no attribute"
             " 'set_value'|"  # AttributeError
             "unhashable type: 'numpy.ndarray'|"  # TypeError
             "No matching signature found|"  # TypeError
-            r"^\[\[\["  # pandas.core.indexing.IndexingError
+            r"^\[\[\[|"  # pandas.core.indexing.IndexingError
+            "Index data must be 1-dimensional"
         )
 
         if (idxr_id == "iloc") or (
@@ -176,10 +160,8 @@ def test_setitem_ndarray_3d(self, index, obj, idxr, idxr_id):
         ):
             idxr[nd3] = 0
         else:
-            with pytest.raises(
-                (ValueError, AttributeError, TypeError, pd.core.indexing.IndexingError),
-                match=msg,
-            ):
+            err = (ValueError, AttributeError)
+            with pytest.raises(err, match=msg):
                 idxr[nd3] = 0
 
     def test_inf_upcast(self):