table_from_frames: assure index is in metas if not range index

Orange/data/pandas_compat.py

@@ -338,6 +338,13 @@ def table_from_frame(df, *, force_nominal=False):
 
 
 def table_from_frames(xdf, ydf, mdf):
+    if not (xdf.index.equals(ydf.index) and xdf.index.equals(mdf.index)):
+        raise ValueError("Indexes not equal. Make sure that all three dataframes have equal index")
+
+    # drop index from x and y - it makes sure that index if not range will be
+    # placed in metas
+    xdf = xdf.reset_index(drop=True)
+    ydf = ydf.reset_index(drop=True)
     dfs = xdf, ydf, mdf
 
     if not all(df.shape[0] == xdf.shape[0] for df in dfs):
@@ -351,12 +358,8 @@ def table_from_frames(xdf, ydf, mdf):
     XYM = (xXYM[0], yXYM[1], mXYM[2])
     domain = Domain(xDomain.attributes, yDomain.class_vars, mDomain.metas)
 
-    indexes = [df.index for df in dfs]
     ids = [
-        int(x[2:])
-        if str(x).startswith("_o") and x[2:].isdigit() and x == y == m
-        else Table.new_id()
-        for x, y, m in zip(*indexes)
+        int(idx[2:]) if str(idx).startswith("_o") and idx[2:].isdigit() else Table.new_id() for idx in mdf.index
     ]
 
     attributes = {}

Orange/data/tests/test_pandas.py

@@ -457,6 +457,33 @@ def test_table_from_frames_not_orange_dataframe(self):
         self.assertEqual(y.columns[0], d.class_var.name)
         self.assertListEqual(m.columns.tolist(), [a.name for a in d.metas])
 
+    def test_table_from_frames_same_index(self):
+        """
+        Test that index column is placed in metas. Function should fail
+        with ValueError when indexes are different
+        """
+        index = np.array(["a", "b"])
+        x = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=["x1", "x2", "x3"], index=index)
+        y = pd.DataFrame([[5], [6]], columns=["y"], index=index)
+        m = pd.DataFrame([[1, 2], [4, 5]], columns=["m1", "m2"], index=index)
+        new_table = Table.from_pandas_dfs(x, y, m)
+
+        # index should be placed in metas
+        np.testing.assert_array_equal(x, new_table.X)
+        np.testing.assert_array_equal(y.values.flatten(), new_table.Y)
+        np.testing.assert_array_equal(np.hstack((index[:, None], m.values.astype("object"))), new_table.metas)
+        d = new_table.domain
+        self.assertListEqual(x.columns.tolist(), [a.name for a in d.attributes])
+        self.assertEqual(y.columns[0], d.class_var.name)
+        self.assertListEqual(["index"] + m.columns.tolist(), [a.name for a in d.metas])
+
+        index2 = np.array(["a", "c"])
+        x = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=["x1", "x2", "x3"], index=index)
+        y = pd.DataFrame([[5], [6]], columns=["y"], index=index2)
+        m = pd.DataFrame([[1, 2], [4, 5]], columns=["m1", "m2"], index=index)
+        with self.assertRaises(ValueError):
+            Table.from_pandas_dfs(x, y, m)
+
 
 class TestTablePandas(unittest.TestCase):
     def setUp(self):
@@ -593,7 +620,7 @@ def test_merge(self):
         table3 = df3.to_orange_table()
 
         self.assertEqual(len(table2), len(table3))
-        self.assertFalse(any(table3.W))
+        self.assertEqual(0, table3.W.size)
         self.assertEqual(self.table.attributes, table3.attributes)
 
         d1 = table2.domain