Fix stubname equal suffix in wide to long function

doc/source/whatsnew/v3.0.0.rst

@@ -647,6 +647,7 @@ Categorical
 
 Datetimelike
 ^^^^^^^^^^^^
+- Bug in :attr:`Series.dt.date` returned datetime dtype on Series with all NaT values; now returns object dtype (:issue:`61188`)
 - Bug in :attr:`is_year_start` where a DateTimeIndex constructed via a date_range with frequency 'MS' wouldn't have the correct year or quarter start attributes (:issue:`57377`)
 - Bug in :class:`DataFrame` raising ``ValueError`` when ``dtype`` is ``timedelta64`` and ``data`` is a list containing ``None`` (:issue:`60064`)
 - Bug in :class:`Timestamp` constructor failing to raise when ``tz=None`` is explicitly specified in conjunction with timezone-aware ``tzinfo`` or data (:issue:`48688`)

pandas/core/indexes/accessors.py

@@ -108,7 +108,9 @@ def _delegate_property_get(self, name: str):
         else:
             index = self._parent.index
         # return the result as a Series
-        return Series(result, index=index, name=self.name).__finalize__(self._parent)
+        return Series(
+            result, index=index, name=self.name, dtype=result.dtype
+        ).__finalize__(self._parent)
 
     def _delegate_property_set(self, name: str, value, *args, **kwargs) -> NoReturn:
         raise ValueError(

pandas/core/reshape/melt.py

@@ -616,6 +616,9 @@ def get_var_names(df, stub: str, sep: str, suffix: str):
         return df.columns[df.columns.str.match(regex)]
 
     def melt_stub(df, stub: str, i, j, value_vars, sep: str):
+        # Ensure value_name and var_name are different when passing to melt
+        j_original = j
+        j = f"{j}_1" if stub == j else j
         newdf = melt(
             df,
             id_vars=i,
@@ -632,7 +635,10 @@ def melt_stub(df, stub: str, i, j, value_vars, sep: str):
             # TODO: anything else to catch?
             pass
 
-        return newdf.set_index(i + [j])
+        newdf = newdf.set_index(i + [j])
+        if j != j_original:
+            newdf.index = newdf.index.set_names(j_original, level=-1)
+        return newdf
 
     if not is_list_like(stubnames):
         stubnames = [stubnames]

pandas/tests/reshape/test_melt.py

@@ -1241,6 +1241,33 @@ def test_missing_stubname(self, any_string_dtype):
         expected.index = expected.index.set_levels(new_level, level=0)
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize("stubnames", ["year", ["year"]])
+    def test_stubname_equal_suffix(self, stubnames):
+        # https://github.com/pandas-dev/pandas/issues/46939
+        df = DataFrame(
+            {
+                "year1": {0: 4.5, 1: 1.7},
+                "year2": {0: 2.5, 1: 1.2},
+                "X": dict(zip(range(2), range(2, 4))),
+            }
+        )
+        df["id"] = df.index
+        result = wide_to_long(
+            df,
+            stubnames=stubnames,
+            i="id",
+            j="year",
+        )
+        expected = DataFrame(
+            [[2, 4.5], [3, 1.7], [2, 2.5], [3, 1.2]],
+            columns=["X", "year"],
+            index=pd.MultiIndex.from_arrays(
+                [[0, 1, 0, 1], [1, 1, 2, 2]],
+                names=["id", "year"],
+            ),
+        )
+        tm.assert_frame_equal(result, expected)
+
 
 def test_wide_to_long_string_columns(string_storage):
     # GH 57066

pandas/tests/series/indexing/test_datetime.py

@@ -491,3 +491,23 @@ def test_compare_datetime_with_all_none():
     result = ser > ser2
     expected = Series([False, False])
     tm.assert_series_equal(result, expected)
+
+
+def test_dt_date_dtype_all_nat_is_object():
+    # Ensure .dt.date on all-NaT Series returns object dtype and not datetime64
+    # GH#61188
+    s = Series([pd.NaT, pd.NaT], dtype="datetime64[s]")
+    result = s.dt.date
+
+    expected = Series([pd.NaT, pd.NaT], dtype=object)
+
+    tm.assert_series_equal(result, expected)
+
+
+def test_dt_date_all_nat_le_date():
+    # All-NaT Series should not raise error when compared to a datetime.date
+    # GH#61188
+    s = Series([pd.NaT, pd.NaT], dtype="datetime64[s]")
+    result = s.dt.date <= datetime.now().date()
+    expected = Series([False, False])
+    tm.assert_series_equal(result, expected)