Updated infer_dtype docstring

doc/source/whatsnew/v3.0.0.rst

@@ -694,6 +694,7 @@ Interval
 Indexing
 ^^^^^^^^
 - Bug in :meth:`DataFrame.__getitem__` returning modified columns when called with ``slice`` in Python 3.12 (:issue:`57500`)
+- Bug in :meth:`DataFrame.__getitem__` when slicing a :class:`DataFrame` with many rows raised an ``OverflowError`` (:issue:`59531`)
 - Bug in :meth:`DataFrame.from_records` throwing a ``ValueError`` when passed an empty list in ``index`` (:issue:`58594`)
 - Bug in :meth:`DataFrame.loc` with inconsistent behavior of loc-set with 2 given indexes to Series (:issue:`59933`)
 - Bug in :meth:`Index.get_indexer` and similar methods when ``NaN`` is located at or after position 128 (:issue:`58924`)
@@ -713,7 +714,7 @@ MultiIndex
 - :func:`MultiIndex.get_level_values` accessing a :class:`DatetimeIndex` does not carry the frequency attribute along (:issue:`58327`, :issue:`57949`)
 - Bug in :class:`DataFrame` arithmetic operations in case of unaligned MultiIndex columns (:issue:`60498`)
 - Bug in :class:`DataFrame` arithmetic operations with :class:`Series` in case of unaligned MultiIndex (:issue:`61009`)
--
+- Bug in :meth:`MultiIndex.from_tuples` causing wrong output with input of type tuples having NaN values (:issue:`60695`, :issue:`60988`)
 
 I/O
 ^^^

pandas/_libs/lib.pyx

@@ -502,7 +502,7 @@ def has_only_ints_or_nan(const floating[:] arr) -> bool:
     return True
 
 
-def maybe_indices_to_slice(ndarray[intp_t, ndim=1] indices, int max_len):
+def maybe_indices_to_slice(ndarray[intp_t, ndim=1] indices, intp_t max_len):
     cdef:
         Py_ssize_t i, n = len(indices)
         intp_t k, vstart, vlast, v
@@ -1518,7 +1518,7 @@ cdef object _try_infer_map(object dtype):
 
 def infer_dtype(value: object, skipna: bool = True) -> str:
     """
-    Return a string label of the type of a scalar or list-like of values.
+    Return a string label of the type of the elements in a list-like input.
 
     This method inspects the elements of the provided input and determines
     classification of its data type. It is particularly useful for
@@ -1527,7 +1527,7 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
 
     Parameters
     ----------
-    value : scalar, list, ndarray, or pandas type
+    value : list, ndarray, or pandas type
         The input data to infer the dtype.
     skipna : bool, default True
         Ignore NaN values when inferring the type.
@@ -1573,6 +1573,7 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
 
     Notes
     -----
+    - The value parameter must be an iterable; scalar inputs are not supported.
     - 'mixed' is the catchall for anything that is not otherwise
       specialized
     - 'mixed-integer-float' are floats and integers

pandas/_libs/tslibs/offsets.pyx

@@ -5108,8 +5108,8 @@ def _warn_about_deprecated_aliases(name: str, is_period: bool) -> str:
         warnings.warn(
             f"\'{name}\' is deprecated and will be removed "
             f"in a future version, please use "
-            f"\'{c_PERIOD_AND_OFFSET_DEPR_FREQSTR.get(name)}\'"
-            f" instead.",
+            f"\'{c_PERIOD_AND_OFFSET_DEPR_FREQSTR.get(name)}\' "
+            f"instead.",
             FutureWarning,
             stacklevel=find_stack_level(),
             )
@@ -5122,8 +5122,8 @@ def _warn_about_deprecated_aliases(name: str, is_period: bool) -> str:
             warnings.warn(
                 f"\'{name}\' is deprecated and will be removed "
                 f"in a future version, please use "
-                f"\'{_name}\'"
-                f" instead.",
+                f"\'{_name}\' "
+                f"instead.",
                 FutureWarning,
                 stacklevel=find_stack_level(),
                 )

pandas/core/algorithms.py

@@ -1647,6 +1647,8 @@ def map_array(
         If the function returns a tuple with more than one element
         a MultiIndex will be returned.
     """
+    from pandas import Index
+
     if na_action not in (None, "ignore"):
         msg = f"na_action must either be 'ignore' or None, {na_action} was passed"
         raise ValueError(msg)
@@ -1676,6 +1678,10 @@ def map_array(
 
             if len(mapper) == 0:
                 mapper = Series(mapper, dtype=np.float64)
+            elif isinstance(mapper, dict):
+                mapper = Series(
+                    mapper.values(), index=Index(mapper.keys(), tupleize_cols=False)
+                )
             else:
                 mapper = Series(mapper)
 

pandas/core/indexes/multi.py

@@ -9,6 +9,7 @@
     Sequence,
 )
 from functools import wraps
+from itertools import zip_longest
 from sys import getsizeof
 from typing import (
     TYPE_CHECKING,
@@ -588,7 +589,7 @@ def from_tuples(
         elif isinstance(tuples, list):
             arrays = list(lib.to_object_array_tuples(tuples).T)
         else:
-            arrs = zip(*tuples)
+            arrs = zip_longest(*tuples, fillvalue=np.nan)
             arrays = cast(list[Sequence[Hashable]], arrs)
 
         return cls.from_arrays(arrays, sortorder=sortorder, names=names)

pandas/tests/indexes/multi/test_constructors.py

@@ -410,6 +410,19 @@ def test_from_tuples_with_tuple_label():
     tm.assert_frame_equal(expected, result)
 
 
+@pytest.mark.parametrize(
+    "keys, expected",
+    [
+        ((("l1",), ("l1", "l2")), (("l1", np.nan), ("l1", "l2"))),
+        ((("l1", "l2"), ("l1",)), (("l1", "l2"), ("l1", np.nan))),
+    ],
+)
+def test_from_tuples_with_various_tuple_lengths(keys, expected):
+    # GH 60695
+    idx = MultiIndex.from_tuples(keys)
+    assert tuple(idx) == expected
+
+
 # ----------------------------------------------------------------------------
 # from_product
 # ----------------------------------------------------------------------------

pandas/tests/series/test_constructors.py

@@ -1441,10 +1441,17 @@ def test_constructor_tuple_of_tuples(self):
         s = Series(data)
         assert tuple(s) == data
 
-    def test_constructor_dict_of_tuples(self):
-        data = {(1, 2): 3, (None, 5): 6}
+    @pytest.mark.parametrize(
+        "data, expected_values, expected_index",
+        [
+            ({(1, 2): 3, (None, 5): 6}, [3, 6], [(1, 2), (None, 5)]),
+            ({(1,): 3, (4, 5): 6}, [3, 6], [(1, None), (4, 5)]),
+        ],
+    )
+    def test_constructor_dict_of_tuples(self, data, expected_values, expected_index):
+        # GH 60695
         result = Series(data).sort_values()
-        expected = Series([3, 6], index=MultiIndex.from_tuples([(1, 2), (None, 5)]))
+        expected = Series(expected_values, index=MultiIndex.from_tuples(expected_index))
         tm.assert_series_equal(result, expected)
 
     # https://github.com/pandas-dev/pandas/issues/22698
@@ -1860,23 +1867,30 @@ class A(OrderedDict):
         series = Series(A(data))
         tm.assert_series_equal(series, expected)
 
-    def test_constructor_dict_multiindex(self):
-        d = {("a", "a"): 0.0, ("b", "a"): 1.0, ("b", "c"): 2.0}
-        _d = sorted(d.items())
-        result = Series(d)
-        expected = Series(
-            [x[1] for x in _d], index=MultiIndex.from_tuples([x[0] for x in _d])
-        )
-        tm.assert_series_equal(result, expected)
+    @pytest.mark.parametrize(
+        "data, expected_index_multi",
+        [
+            ({("a", "a"): 0.0, ("b", "a"): 1.0, ("b", "c"): 2.0}, True),
+            ({("a",): 0.0, ("a", "b"): 1.0}, True),
+            ({"z": 111.0, ("a", "a"): 0.0, ("b", "a"): 1.0, ("b", "c"): 2.0}, False),
+        ],
+    )
+    def test_constructor_dict_multiindex(self, data, expected_index_multi):
+        # GH#60695
+        result = Series(data)
 
-        d["z"] = 111.0
-        _d.insert(0, ("z", d["z"]))
-        result = Series(d)
-        expected = Series(
-            [x[1] for x in _d], index=Index([x[0] for x in _d], tupleize_cols=False)
-        )
-        result = result.reindex(index=expected.index)
-        tm.assert_series_equal(result, expected)
+        if expected_index_multi:
+            expected = Series(
+                list(data.values()),
+                index=MultiIndex.from_tuples(list(data.keys())),
+            )
+            tm.assert_series_equal(result, expected)
+        else:
+            expected = Series(
+                list(data.values()),
+                index=Index(list(data.keys())),
+            )
+            tm.assert_series_equal(result, expected)
 
     def test_constructor_dict_multiindex_reindex_flat(self):
         # construction involves reindexing with a MultiIndex corner case