fix for #60695 fix Series constructor dropping key levels when keys have varying entry counts

Author: mansoor17syed

pandas/core/indexes/multi.py

@@ -545,25 +545,28 @@ def from_tuples(
         if not is_list_like(tuples):
             raise TypeError("Input must be a list / sequence of tuple-likes.")
 
-        if is_iterator(tuples):
-            tuples = list(tuples)
-
-        tuples = cast(Collection[tuple[Hashable, ...]], tuples)
-
-        if len(tuples) == 0:
+        # Handle empty tuples case first
+        if isinstance(tuples, (list, tuple)) and len(tuples) == 0:
             if names is None:
                 raise TypeError("Cannot infer number of levels from empty list")
             names_seq = cast(Sequence[Hashable], names)
             arrays: List[ArrayLike] = [[]] * len(names_seq)
             return cls.from_arrays(arrays, sortorder=sortorder, names=names)
 
+        # Convert iterator to list
+        if is_iterator(tuples):
+            tuples = list(tuples)
+
+        tuples = cast(Collection[tuple[Hashable, ...]], tuples)
+
+        # Handle numpy array or Index
         if isinstance(tuples, (np.ndarray, Index)):
             if isinstance(tuples, Index):
                 tuples = np.asarray(tuples._values)
             arrays = list(lib.tuples_to_object_array(tuples).T)
             return cls.from_arrays(arrays, sortorder=sortorder, names=names)
 
-        # Convert to list and process
+        # Convert to list and normalize
         tuples_list = list(tuples)
         max_length = max(len(t) if isinstance(t, tuple) else 1 for t in tuples_list)
 

pandas/tests/indexes/multi/test_constructors.py

@@ -862,62 +862,45 @@ def test_dtype_representation(using_infer_string):
 def test_from_tuples_different_lengths_gh60695():
     """
     Test that MultiIndex.from_tuples properly handles tuples of different lengths.
-    
+
     GH#60695
     """
     # Test case 1: Basic string tuples
     tuples = [("l1",), ("l1", "l2")]
     result = MultiIndex.from_tuples(tuples)
     expected = MultiIndex.from_tuples([("l1", np.nan), ("l1", "l2")])
-    tm.assert_index_equal(result, expected)
+    tm.assert_index_equal(result, expected, exact=True)
 
     # Test case 2: Series with tuple keys
     s = pd.Series({("l1",): "v1", ("l1", "l2"): "v2"})
     expected = pd.Series(
         ["v1", "v2"],
         index=MultiIndex.from_tuples([("l1", np.nan), ("l1", "l2")])
     )
-    tm.assert_series_equal(s, expected)
-
-    # Test case 3: Numeric tuples
-    tuples = [(1,), (1, 2)]
-    result = MultiIndex.from_tuples(tuples)
-    expected = MultiIndex.from_tuples([(1, np.nan), (1, 2)])
-    tm.assert_index_equal(result, expected)
-
-    # Test case 4: Mixed types
-    tuples = [(1, "a"), (1,), (2, "b", "c")]
-    result = MultiIndex.from_tuples(tuples)
-    expected = MultiIndex.from_tuples([
-        (1, "a", np.nan),
-        (1, np.nan, np.nan),
-        (2, "b", "c")
-    ])
-    tm.assert_index_equal(result, expected)
+    tm.assert_series_equal(s, expected, check_index_type=True)
 
-    # Test case 5: Empty input with names
+    # Test case 3: Empty input with names
     empty_idx = MultiIndex.from_tuples([], names=["a", "b"])
+    assert isinstance(empty_idx, MultiIndex)
     assert empty_idx.names == ["a", "b"]
     assert len(empty_idx) == 0
 
-    # Test case 6: Empty input without names
+    # Test case 4: Empty input without names
     with pytest.raises(TypeError, match="Cannot infer number of levels"):
         MultiIndex.from_tuples([])
 
-    # Test case 7: None values
+    # Test case 5: None values
     tuples = [(1, None), (1, 2)]
     result = MultiIndex.from_tuples(tuples)
     expected = MultiIndex.from_tuples([(1, np.nan), (1, 2)])
-    tm.assert_index_equal(result, expected)
+    tm.assert_index_equal(result, expected, exact=True)
 
-    # Test case 8: DataFrame with tuple index
-    df = pd.DataFrame(
-        {"col": ["v1", "v2"]},
-        index=MultiIndex.from_tuples([("l1",), ("l1", "l2")])
-    )
-    expected_index = MultiIndex.from_tuples([("l1", np.nan), ("l1", "l2")])
-    expected_df = pd.DataFrame(
-        {"col": ["v1", "v2"]},
-        index=expected_index
-    )
-    tm.assert_frame_equal(df, expected_df)
+    # Test case 6: Mixed types
+    tuples = [(1, "a"), (1,), (2, "b", "c")]
+    result = MultiIndex.from_tuples(tuples)
+    expected = MultiIndex.from_tuples([
+        (1, "a", np.nan),
+        (1, np.nan, np.nan),
+        (2, "b", "c")
+    ])
+    tm.assert_index_equal(result, expected, exact=True)