ensuring that np.asarray() simple handles data as objects and doesn't try to do smart things

Author: realead

pandas/core/algorithms.py

@@ -134,7 +134,7 @@ def _ensure_data(values, dtype=None):
         return values, dtype, 'int64'
 
     # we have failed, return object
-    values = np.asarray(values)
+    values = np.asarray(values, dtype=np.object)
     return ensure_object(values), 'object', 'object'
 
 

pandas/tests/test_algos.py

@@ -614,6 +614,24 @@ def test_categorical_from_codes(self):
         result = algos.isin(Sd, St)
         tm.assert_numpy_array_equal(expected, result)
 
+    def test_same_object_is_in(self):
+        # GH 22160
+        # nan is special, because out of a is a doesn't follow a == a
+        comps = ['ss', np.nan]
+        values = [np.nan]
+        expected = np.array([False, True])
+        result = algos.isin(comps, values)
+        tm.assert_numpy_array_equal(expected, result)
+
+    def test_no_cast(self):
+        # GH 22160
+        # ensure 42 is not casted to string
+        comps = ['ss', 42]
+        values = ['42']
+        expected = np.array([False, False])
+        result = algos.isin(comps, values)
+        tm.assert_numpy_array_equal(expected, result)
+
     @pytest.mark.parametrize("empty", [[], Series(), np.array([])])
     def test_empty(self, empty):
         # see gh-16991