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

Author: mansoor17syed

pandas/core/indexes/multi.py

@@ -7,6 +7,7 @@
     Hashable,
     Iterable,
     Sequence,
+    List,
 )
 from functools import wraps
 from sys import getsizeof
@@ -15,6 +16,7 @@
     Any,
     Literal,
     cast,
+    ArrayLike,
 )
 import warnings
 
@@ -517,7 +519,7 @@ def from_arrays(
         )
 
     @classmethod
-    @names_compat
+    @doc(doc_create_index)
     def from_tuples(
         cls,
         tuples: Iterable[tuple[Hashable, ...]],
@@ -529,41 +531,24 @@ 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)
-
-        # handling the empty tuple cases
-        if len(tuples) and all(isinstance(e, tuple) and not e for e in tuples):
-            codes = [np.zeros(len(tuples))]
-            levels = [Index(com.asarray_tuplesafe(tuples, dtype=np.dtype("object")))]
-            return cls(
-                levels=levels,
-                codes=codes,
-                sortorder=sortorder,
-                names=names,
-                verify_integrity=False,
-            )
 
-        arrays: list[Sequence[Hashable]]
-        if len(tuples) == 0:
+        if isinstance(tuples, (list, tuple)) and len(tuples) == 0:
             if names is None:
                 raise TypeError("Cannot infer number of levels from empty list")
-            # error: Argument 1 to "len" has incompatible type "Hashable";
-            # expected "Sized"
-            arrays = [[]] * len(names)  # type: ignore[arg-type]
-        elif isinstance(tuples, (np.ndarray, Index)):
-            if isinstance(tuples, Index):
-                tuples = np.asarray(tuples._values)
-
-            arrays = list(lib.tuples_to_object_array(tuples).T)
-        elif isinstance(tuples, list):
-            arrays = list(lib.to_object_array_tuples(tuples).T)
+            names_seq = cast(Sequence[Hashable], names)
+            arrays: List[ArrayLike] = [[]] * len(names_seq)
+            return cls.from_arrays(arrays, sortorder=sortorder, names=names)
+
+        # Convert to list and normalize
+        tuples_list = [t if isinstance(t, tuple) else (t,) for t in tuples]
+        if not tuples_list:
+            arrays = []
         else:
-            arrs = zip(*tuples)
-            arrays = cast(list[Sequence[Hashable]], arrs)
+            max_length = max(len(t) for t in tuples_list)
+            result_tuples = [
+                t + (np.nan,) * (max_length - len(t)) for t in tuples_list
+            ]
+            arrays = list(lib.to_object_array_tuples(result_tuples).T)
 
         return cls.from_arrays(arrays, sortorder=sortorder, names=names)