try not replacing _from_blocks with _from_array

pandas/core/internals/construction.py

@@ -80,11 +80,15 @@
     ArrayManager,
     SingleArrayManager,
 )
+from pandas.core.internals.blocks import (
+    ensure_block_shape,
+    new_block,
+)
 from pandas.core.internals.managers import (
     BlockManager,
     SingleBlockManager,
-    create_block_manager_from_array,
     create_block_manager_from_arrays,
+    create_block_manager_from_blocks,
 )
 
 if TYPE_CHECKING:
@@ -347,29 +351,42 @@ def ndarray_to_mgr(
 
         return ArrayManager(arrays, [index, columns], verify_integrity=False)
 
-    array = values.T
+    values = values.T
 
     # if we don't have a dtype specified, then try to convert objects
     # on the entire block; this is to convert if we have datetimelike's
     # embedded in an object type
-    if dtype is None and is_object_dtype(array.dtype):
-        if array.ndim == 2 and array.shape[0] != 1:
+    if dtype is None and is_object_dtype(values.dtype):
+
+        if values.ndim == 2 and values.shape[0] != 1:
             # transpose and separate blocks
-            maybe_datetime = [
-                maybe_infer_to_datetimelike(instance) for instance in array
-            ]
+
+            dtlike_vals = [maybe_infer_to_datetimelike(row) for row in values]
             # don't convert (and copy) the objects if no type inference occurs
             if any(
-                not is_dtype_equal(instance.dtype, array.dtype)
-                for instance in maybe_datetime
+                not is_dtype_equal(instance.dtype, values.dtype)
+                for instance in dtlike_vals
             ):
-                return create_block_manager_from_arrays(
-                    maybe_datetime, columns, [columns, index]
-                )
+                dvals_list = [ensure_block_shape(dval, 2) for dval in dtlike_vals]
+                block_values = [
+                    new_block(dvals_list[n], placement=n, ndim=2)
+                    for n in range(len(dvals_list))
+                ]
+            else:
+                nb = new_block(values, placement=slice(len(columns)), ndim=2)
+                block_values = [nb]
         else:
-            array = maybe_infer_to_datetimelike(array)
+            datelike_vals = maybe_infer_to_datetimelike(values)
+            nb = new_block(datelike_vals, placement=slice(len(columns)), ndim=2)
+            block_values = [nb]
+    else:
+        nb = new_block(values, placement=slice(len(columns)), ndim=2)
+        block_values = [nb]
+
+    if len(columns) == 0:
+        block_values = []
 
-    return create_block_manager_from_array(array, [columns, index])
+    return create_block_manager_from_blocks(block_values, [columns, index])
 
 
 def _check_values_indices_shape_match(

pandas/core/internals/managers.py

@@ -1753,26 +1753,6 @@ def create_block_manager_from_arrays(
     return mgr
 
 
-def create_block_manager_from_array(
-    array,
-    axes: list[Index],
-    consolidate: bool = True,
-) -> BlockManager:
-    assert isinstance(axes, list)
-    assert all(isinstance(x, Index) for x in axes)
-
-    array = _extract_array(array)
-
-    try:
-        block = new_block(values=array, placement=slice(0, len(axes[0])), ndim=2)
-        mgr = BlockManager([block], axes)
-    except ValueError as e:
-        raise construction_error(array.shape[0], array.shape[1:], axes, e)
-    if consolidate:
-        mgr._consolidate_inplace()
-    return mgr
-
-
 def construction_error(
     tot_items: int,
     block_shape: Shape,