FIX-modin-project#1679: Assignment df.loc["row"]["col"] fixed in case…

… of one row (modin-project#1951)

Signed-off-by: Dmitry Chigarev <dmitry.chigarev@intel.com>

modin/engines/base/frame/partition_manager.py

@@ -302,6 +302,10 @@ def concat(cls, axis, left_parts, right_parts):
             A new BaseFrameManager object, the type of object that called this.
         """
         if type(right_parts) is list:
+            # `np.array` with partitions of empty ModinFrame has a shape (0,)
+            # but `np.concatenate` can concatenate arrays only if its shapes at
+            # specified axis are equals, so filtering empty frames to avoid concat error
+            right_parts = [o for o in right_parts if o.size != 0]
             return np.concatenate([left_parts] + right_parts, axis=axis)
         else:
             return np.append(left_parts, right_parts, axis=axis)

modin/pandas/test/test_dataframe.py

@@ -4677,26 +4677,16 @@ def test_loc_multi_index(self):
         df_equals(modin_df.loc[modin_df.index], pandas_df.loc[pandas_df.index])
         df_equals(modin_df.loc[modin_df.index[:7]], pandas_df.loc[pandas_df.index[:7]])
 
-    def test_loc_assignment(self):
-        modin_df = pd.DataFrame(
-            index=["row1", "row2", "row3"], columns=["col1", "col2"]
-        )
-        pandas_df = pandas.DataFrame(
-            index=["row1", "row2", "row3"], columns=["col1", "col2"]
-        )
-        modin_df.loc["row1"]["col1"] = 11
-        modin_df.loc["row2"]["col1"] = 21
-        modin_df.loc["row3"]["col1"] = 31
-        modin_df.loc["row1"]["col2"] = 12
-        modin_df.loc["row2"]["col2"] = 22
-        modin_df.loc["row3"]["col2"] = 32
-        pandas_df.loc["row1"]["col1"] = 11
-        pandas_df.loc["row2"]["col1"] = 21
-        pandas_df.loc["row3"]["col1"] = 31
-        pandas_df.loc["row1"]["col2"] = 12
-        pandas_df.loc["row2"]["col2"] = 22
-        pandas_df.loc["row3"]["col2"] = 32
-        df_equals(modin_df, pandas_df)
+    @pytest.mark.parametrize("index", [["row1", "row2", "row3"], ["row1"]])
+    @pytest.mark.parametrize("columns", [["col1", "col2"], ["col1"]])
+    def test_loc_assignment(self, index, columns):
+        md_df, pd_df = create_test_dfs(index=index, columns=columns)
+        for i, ind in enumerate(index):
+            for j, col in enumerate(columns):
+                value_to_assign = int(str(i) + str(j))
+                md_df.loc[ind][col] = value_to_assign
+                pd_df.loc[ind][col] = value_to_assign
+        df_equals(md_df, pd_df)
 
     @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
     def test_loc_nested_assignment(self, data):