added test case for iloc function if it returns the same output for b…

pandas/core/indexing.py

@@ -44,6 +44,7 @@
     isna,
 )
 
+from pandas.core.arrays.integer import IntegerArray
 import pandas.core.common as com
 from pandas.core.construction import array as pd_array
 from pandas.core.indexers import (
@@ -1588,10 +1589,11 @@ def _setitem_with_indexer(self, indexer, value, name="iloc"):
         BlockManager methods, see GH#12991, GH#22046, GH#15686.
         """
         info_axis = self.obj._info_axis_number
-
         # maybe partial set
         take_split_path = not self.obj._mgr.is_single_block
 
+        value = np.array(value) if isinstance(value, IntegerArray) else value
+
         # if there is only one block/type, still have to take split path
         # unless the block is one-dimensional or it can hold the value
         if (
@@ -1705,7 +1707,6 @@ def _setitem_with_indexer_split_path(self, indexer, value, name: str):
         """
         # Above we only set take_split_path to True for 2D cases
         assert self.ndim == 2
-
         if not isinstance(indexer, tuple):
             indexer = _tuplify(self.ndim, indexer)
         if len(indexer) > self.ndim:
@@ -1716,8 +1717,8 @@ def _setitem_with_indexer_split_path(self, indexer, value, name: str):
         if (isinstance(value, ABCSeries) and name != "iloc") or isinstance(value, dict):
             from pandas import Series
 
+            print("value is ABCseries")
             value = self._align_series(indexer, Series(value))
-
         # Ensure we have something we can iterate over
         info_axis = indexer[1]
         ilocs = self._ensure_iterable_column_indexer(info_axis)
@@ -1731,6 +1732,7 @@ def _setitem_with_indexer_split_path(self, indexer, value, name: str):
         if is_list_like_indexer(value) and getattr(value, "ndim", 1) > 0:
 
             if isinstance(value, ABCDataFrame):
+                print("value is ABCDataFrame")
                 self._setitem_with_indexer_frame_value(indexer, value, name)
 
             elif np.ndim(value) == 2:

pandas/tests/indexing/multiindex/test_iloc.py

@@ -1,6 +1,7 @@
 import numpy as np
 import pytest
 
+import pandas as pd
 from pandas import (
     DataFrame,
     MultiIndex,
@@ -73,6 +74,53 @@ def test_iloc_getitem_multiple_items():
     tm.assert_frame_equal(result, expected)
 
 
+def test_iloc_pd_arr_value():
+    # test if iloc returns the same output for numpy array input and integer array input
+    df = DataFrame(
+        data={
+            "col1": [1, 2, 3, 4],
+            "col2": [3, 4, 5, 6],
+            "col3": [6, 7, 8, 9],
+        }
+    )
+    df_np = df.copy()
+    df_pd = df.copy()
+    df_int = df.copy()
+
+    pd_arr = pd.array([1, 2, 3])
+    np_arr = np.array([1, 2, 3])
+    int_arr = [1, 2, 3]
+    df_pd.iloc[[1, 2, 3]] = pd_arr
+    df_np.iloc[[1, 2, 3]] = np_arr
+    df_int.iloc[[1, 2, 3]] = int_arr
+
+    tm.assert_frame_equal(df_pd, df_np) and tm.assert_frame_equal(df_int, df_np)
+
+
+def test_iloc_pd_arr_value2():
+    # test if iloc returns the same output for numpy array input and integer array input
+    df = DataFrame(
+        data={
+            "col1": [1, 2, 3, 4],
+            "col2": [3, 4, 5, 6],
+            "col3": [6, 7, 8, 9],
+        }
+    )
+    df_np = df.copy()
+    df_pd = df.copy()
+    df_int = df.copy()
+
+    pd_arr = pd.array([1, 2, 3])
+    np_arr = np.array([1, 2, 3])
+    int_arr = [1, 2, 3]
+
+    df_pd.iloc[[1, 2, 3], :] = pd_arr
+    df_np.iloc[[1, 2, 3], :] = np_arr
+    df_int.iloc[[1, 2, 3], :] = int_arr
+
+    tm.assert_frame_equal(df_pd, df_np) and tm.assert_frame_equal(df_int, df_np)
+
+
 def test_iloc_getitem_labels():
     # this is basically regular indexing
     arr = np.random.randn(4, 3)