Replaced np.vectorize() with any() for minor performance improvement and add new test cases

Author: akj2018

pandas/core/algorithms.py

@@ -552,9 +552,8 @@ def isin(comps: ListLike, values: ListLike) -> npt.NDArray[np.bool_]:
     # Ensure values don't contain <NA>, otherwise it throws exception with np.in1d
     values_contains_NA = False
 
-    if values.size != 0:  
-        vectorized_check = np.vectorize(lambda v: v is NA)
-        values_contains_NA = vectorized_check(values).any()
+    if comps_array.dtype != object and len(values) <= 26:  
+        values_contains_NA = any(v is NA for v in values)
 
     if (
         len(comps_array) > _MINIMUM_COMP_ARR_LEN

pandas/tests/series/methods/test_isin.py

@@ -214,7 +214,9 @@ def test_isin_large_series_mixed_dtypes_and_nan(monkeypatch):
 @pytest.mark.parametrize("dtype, data, values, expected", [
     ("boolean", [pd.NA, False, True], [False, pd.NA], [True, True, False]),
     ("Int64", [pd.NA, 2, 1], [1, pd.NA], [True, False, True]),
-    ("Float64", [20.0, 30.0, pd.NA], [pd.NA], [False, False, True])
+    ("boolean", [pd.NA, False, True], [pd.NA, True, 'a', 20], [True, False, True]),
+    ("boolean", [pd.NA, False, True], [], [False, False, False]),
+    ("Float64", [20.0, 30.0, pd.NA], [pd.NA], [False, False, True]),
 ])
 def test_isin_large_series_and_pdNA(dtype, data, values, expected, monkeypatch):
     # https://github.com/pandas-dev/pandas/issues/60678