Fix test cases

Author: halogen22

pandas/core/arrays/base.py

@@ -2511,8 +2511,9 @@ def _mode(self, dropna: bool = True) -> Self:
             Sorted, if possible.
         """
         # error: Incompatible return value type (got "Union[ExtensionArray,
-        # ndarray[Any, Any]]", expected "Self")
-        return mode(self, dropna=dropna)  # type: ignore[return-value]
+        # Tuple[np.ndarray, npt.NDArray[np.bool_]]", expected "Self")
+        result, _ = mode(self, dropna=dropna)
+        return result
 
     def __array_ufunc__(self, ufunc: np.ufunc, method: str, *inputs, **kwargs):
         if any(

pandas/tests/test_algos.py

@@ -1831,7 +1831,8 @@ def test_pct_max_many_rows(self):
 class TestMode:
     def test_no_mode(self):
         exp = Series([], dtype=np.float64, index=Index([], dtype=int))
-        tm.assert_numpy_array_equal(algos.mode(np.array([])), exp.values)
+        result, _ = algos.mode(np.array([]))
+        tm.assert_numpy_array_equal(result, exp.values)
 
     def test_mode_single(self, any_real_numpy_dtype):
         # GH 15714
@@ -1843,20 +1844,24 @@ def test_mode_single(self, any_real_numpy_dtype):
 
         ser = Series(data_single, dtype=any_real_numpy_dtype)
         exp = Series(exp_single, dtype=any_real_numpy_dtype)
-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+        result, _ = algos.mode(ser.values)
+        tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
         ser = Series(data_multi, dtype=any_real_numpy_dtype)
         exp = Series(exp_multi, dtype=any_real_numpy_dtype)
-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+        result, _ = algos.mode(ser.values)
+        tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
     def test_mode_obj_int(self):
         exp = Series([1], dtype=int)
-        tm.assert_numpy_array_equal(algos.mode(exp.values), exp.values)
+        result, _ = algos.mode(exp.values)
+        tm.assert_numpy_array_equal(result, exp.values)
 
         exp = Series(["a", "b", "c"], dtype=object)
-        tm.assert_numpy_array_equal(algos.mode(exp.values), exp.values)
+        result, _ = algos.mode(exp.values)
+        tm.assert_numpy_array_equal(result, exp.values)
 
     def test_number_mode(self, any_real_numpy_dtype):
         exp_single = [1]
@@ -1867,12 +1872,14 @@ def test_number_mode(self, any_real_numpy_dtype):
 
         ser = Series(data_single, dtype=any_real_numpy_dtype)
         exp = Series(exp_single, dtype=any_real_numpy_dtype)
-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+        result, _ = algos.mode(ser.values)
+        tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
         ser = Series(data_multi, dtype=any_real_numpy_dtype)
         exp = Series(exp_multi, dtype=any_real_numpy_dtype)
-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+        result, _ = algos.mode(ser.values)
+        tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
     def test_strobj_mode(self):
@@ -1881,7 +1888,8 @@ def test_strobj_mode(self):
 
         ser = Series(data, dtype="c")
         exp = Series(exp, dtype="c")
-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+        result, _ = algos.mode(ser.values)
+        tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
     @pytest.mark.parametrize("dt", [str, object])
@@ -1891,10 +1899,11 @@ def test_strobj_multi_char(self, dt, using_infer_string):
 
         ser = Series(data, dtype=dt)
         exp = Series(exp, dtype=dt)
+        result, _ = algos.mode(ser.values)
         if using_infer_string and dt is str:
-            tm.assert_extension_array_equal(algos.mode(ser.values), exp.values)
+            tm.assert_extension_array_equal(result, exp.values)
         else:
-            tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+            tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
     def test_datelike_mode(self):
@@ -1928,18 +1937,21 @@ def test_timedelta_mode(self):
     def test_mixed_dtype(self):
         exp = Series(["foo"], dtype=object)
         ser = Series([1, "foo", "foo"])
-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+        result, _ = algos.mode(ser.values)
+        tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
     def test_uint64_overflow(self):
         exp = Series([2**63], dtype=np.uint64)
         ser = Series([1, 2**63, 2**63], dtype=np.uint64)
-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+        result, _ = algos.mode(ser.values)
+        tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
         exp = Series([1, 2**63], dtype=np.uint64)
         ser = Series([1, 2**63], dtype=np.uint64)
-        tm.assert_numpy_array_equal(algos.mode(ser.values), exp.values)
+        result, _ = algos.mode(ser.values)
+        tm.assert_numpy_array_equal(result, exp.values)
         tm.assert_series_equal(ser.mode(), exp)
 
     def test_categorical(self):
@@ -1961,15 +1973,18 @@ def test_categorical(self):
     def test_index(self):
         idx = Index([1, 2, 3])
         exp = Series([1, 2, 3], dtype=np.int64)
-        tm.assert_numpy_array_equal(algos.mode(idx), exp.values)
+        result, _ = algos.mode(idx)
+        tm.assert_numpy_array_equal(result, exp.values)
 
         idx = Index([1, "a", "a"])
         exp = Series(["a"], dtype=object)
-        tm.assert_numpy_array_equal(algos.mode(idx), exp.values)
+        result, _ = algos.mode(idx)
+        tm.assert_numpy_array_equal(result, exp.values)
 
         idx = Index([1, 1, 2, 3, 3])
         exp = Series([1, 3], dtype=np.int64)
-        tm.assert_numpy_array_equal(algos.mode(idx), exp.values)
+        result, _ = algos.mode(idx)
+        tm.assert_numpy_array_equal(result, exp.values)
 
         idx = Index(
             ["1 day", "1 day", "-1 day", "-1 day 2 min", "2 min", "2 min"],