BUG : fix Series.mode throwing exception with dropna=False and no nul…

doc/source/whatsnew/v3.0.0.rst

@@ -572,6 +572,7 @@ Other
 - Bug in :meth:`DataFrame.where` where using a non-bool type array in the function would return a ``ValueError`` instead of a ``TypeError`` (:issue:`56330`)
 - Bug in :meth:`Index.sort_values` when passing a key function that turns values into tuples, e.g. ``key=natsort.natsort_key``, would raise ``TypeError`` (:issue:`56081`)
 - Bug in :meth:`Series.diff` allowing non-integer values for the ``periods`` argument. (:issue:`56607`)
+- Bug in :meth:`Series.mode` where an exception was raised when taking the mode with nullable types with no null values in the series. (:issue:`58926`)
 - Bug in :meth:`Series.rank` that doesn't preserve missing values for nullable integers when ``na_option='keep'``. (:issue:`56976`)
 - Bug in :meth:`Series.replace` and :meth:`DataFrame.replace` inconsistently replacing matching instances when ``regex=True`` and missing values are present. (:issue:`56599`)
 - Bug in Dataframe Interchange Protocol implementation was returning incorrect results for data buffers' associated dtype, for string and datetime columns (:issue:`54781`)

pandas/_libs/hashtable_func_helper.pxi.in

@@ -443,7 +443,7 @@ def mode(ndarray[htfunc_t] values, bint dropna, const uint8_t[:] mask=None):
 
     if na_counter > 0:
         res_mask = np.zeros(j+1, dtype=np.bool_)
-        res_mask[j] = True
+        res_mask[j] = (na_counter == max_count)
     return modes[:j + 1], res_mask
 
 

pandas/core/arrays/masked.py

@@ -1093,7 +1093,13 @@ def _mode(self, dropna: bool = True) -> Self:
             result = mode(self._data, dropna=dropna, mask=self._mask)
             res_mask = np.zeros(result.shape, dtype=np.bool_)
         else:
-            result, res_mask = mode(self._data, dropna=dropna, mask=self._mask)
+            res_tuple = mode(self._data, dropna=dropna, mask=self._mask)
+            if len(res_tuple) == 2:
+                result = res_tuple[0]
+                res_mask = res_tuple[1]
+            else:
+                result = res_tuple
+                res_mask = np.zeros(result.shape, dtype=np.bool_)
         result = type(self)(result, res_mask)  # type: ignore[arg-type]
         return result[result.argsort()]
 

pandas/tests/series/test_reductions.py

@@ -51,6 +51,24 @@ def test_mode_nullable_dtype(any_numeric_ea_dtype):
     tm.assert_series_equal(result, expected)
 
 
+def test_mode_nullable_dtype_edge_case(any_numeric_ea_dtype):
+    # GH##58926
+    ser = Series([1, 1, 2, 3], dtype=any_numeric_ea_dtype)
+    result = ser.mode(dropna=False)
+    expected = Series([1], dtype=any_numeric_ea_dtype)
+    tm.assert_series_equal(result, expected)
+
+    ser2 = Series([1, 1, 2, 3, pd.NA], dtype=any_numeric_ea_dtype)
+    result = ser2.mode(dropna=False)
+    expected = Series([1], dtype=any_numeric_ea_dtype)
+    tm.assert_series_equal(result, expected)
+
+    ser3 = Series([1, pd.NA, pd.NA], dtype=any_numeric_ea_dtype)
+    result = ser3.mode(dropna=False)
+    expected = Series([pd.NA], dtype=any_numeric_ea_dtype)
+    tm.assert_series_equal(result, expected)
+
+
 def test_mode_infer_string():
     # GH#56183
     pytest.importorskip("pyarrow")