put conversion to ndarray in make_block

Author: shantanu-gontia

pandas/core/frame.py

@@ -3620,11 +3620,6 @@ def reindexer(value):
             value = cast_scalar_to_array(len(self.index), value)
             value = maybe_cast_to_datetime(value, infer_dtype)
 
-        # convert pandas array to numpy array
-        if isinstance(value, ABCPandasArray):
-            value = value.to_numpy()
-            return np.atleast_2d(np.asarray(value))
-
         # return internal types directly
         if is_extension_type(value) or is_extension_array_dtype(value):
             return value

pandas/core/internals/blocks.py

@@ -3035,6 +3035,8 @@ def make_block(values, placement, klass=None, ndim=None, dtype=None,
     # For now, blocks should be backed by ndarrays when possible.
     if isinstance(values, ABCPandasArray):
         values = values.to_numpy()
+        if ndim and ndim > 1:
+            values = np.atleast_2d(values)
 
     if isinstance(dtype, PandasDtype):
         dtype = dtype.numpy_dtype

pandas/tests/internals/test_internals.py

@@ -17,7 +17,8 @@
     SparseArray)
 import pandas.core.algorithms as algos
 from pandas.core.arrays import DatetimeArray, TimedeltaArray
-from pandas.core.internals import BlockManager, SingleBlockManager, make_block
+from pandas.core.internals import (
+    BlockManager, ObjectBlock, SingleBlockManager, make_block)
 import pandas.util.testing as tm
 from pandas.util.testing import (
     assert_almost_equal, assert_frame_equal, assert_series_equal, randn)
@@ -1318,4 +1319,6 @@ def test_add_column_with_pandas_array():
     df['c'] = pd.array([1, 2, None, 3])
     df2 = pd.DataFrame({'a': [1, 2, 3, 4], 'b': ['a', 'b', 'c', 'd'],
                         'c': pd.array([1, 2, None, 3])})
+    assert(df2['c']._data.blocks[0].__class__ == ObjectBlock)
+    assert(df['c']._data.blocks[0].__class__ == ObjectBlock)
     assert_frame_equal(df, df2)