FIX-modin-project#1556: Fix support for nested assignment with loc/…

…`iloc` (modin-project#1788)

Signed-off-by: Devin Petersohn <devin.petersohn@gmail.com>

modin/pandas/series.py

@@ -132,6 +132,15 @@ def _validate_dtypes_min_max(self, axis, numeric_only):
     def _validate_dtypes(self, numeric_only=False):
         pass
 
+    def _update_inplace(self, new_query_compiler):
+        super(Series, self)._update_inplace(new_query_compiler=new_query_compiler)
+        # Propagate changes back to parent so that column in dataframe had the same contents
+        if self._parent is not None:
+            if self._parent_axis == 0:
+                self._parent.loc[self.name] = self
+            else:
+                self._parent[self.name] = self
+
     def _create_or_update_from_compiler(self, new_query_compiler, inplace=False):
         """Returns or updates a DataFrame given new query_compiler"""
         assert (
@@ -329,12 +338,6 @@ def __setitem__(self, key, value):
         self._create_or_update_from_compiler(
             self._query_compiler.setitem(1, key, value), inplace=True
         )
-        # Propagate changes back to parent so that column in dataframe had the same contents
-        if self._parent is not None:
-            if self._parent_axis == 0:
-                self._parent.loc[self.name] = self
-            else:
-                self._parent[self.name] = self
 
     def __sub__(self, right):
         return self.sub(right)

modin/pandas/test/test_dataframe.py

@@ -4593,6 +4593,21 @@ def test_loc_assignment(self):
         pandas_df.loc["row3"]["col2"] = 32
         df_equals(modin_df, pandas_df)
 
+    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
+    def test_loc_nested_assignment(self, data):
+        modin_df = pd.DataFrame(data)
+        pandas_df = pandas.DataFrame(data)
+        key1 = modin_df.columns[0]
+        key2 = modin_df.columns[1]
+
+        modin_df[key1].loc[0] = 500
+        pandas_df[key1].loc[0] = 500
+        df_equals(modin_df, pandas_df)
+
+        modin_df[key2].loc[0] = None
+        pandas_df[key2].loc[0] = None
+        df_equals(modin_df, pandas_df)
+
     def test_iloc_assignment(self):
         modin_df = pd.DataFrame(
             index=["row1", "row2", "row3"], columns=["col1", "col2"]
@@ -4614,6 +4629,21 @@ def test_iloc_assignment(self):
         pandas_df.iloc[2]["col2"] = 32
         df_equals(modin_df, pandas_df)
 
+    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
+    def test_iloc_nested_assignment(self, data):
+        modin_df = pd.DataFrame(data)
+        pandas_df = pandas.DataFrame(data)
+        key1 = modin_df.columns[0]
+        key2 = modin_df.columns[1]
+
+        modin_df[key1].iloc[0] = 500
+        pandas_df[key1].iloc[0] = 500
+        df_equals(modin_df, pandas_df)
+
+        modin_df[key2].iloc[0] = None
+        pandas_df[key2].iloc[0] = None
+        df_equals(modin_df, pandas_df)
+
     @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
     def test_pop(self, request, data):
         modin_df = pd.DataFrame(data)