solving issue#34125, now the isin function is more consistent when comparing a int df with a string value on isin comparation

Author: gabrielvf1

pandas/core/algorithms.py

@@ -428,8 +428,14 @@ def isin(comps: AnyArrayLike, values: AnyArrayLike) -> np.ndarray:
         # TODO(extension)
         # handle categoricals
         return comps.isin(values)  # type: ignore
+    try:
+        if comps.dtype.name == 'int64':
+            comps, dtype = _ensure_data(comps, dtype=object)
+        else:
+            comps, dtype = _ensure_data(comps)
+    except:
+        comps, dtype = _ensure_data(comps)
 
-    comps, dtype = _ensure_data(comps)
     values, _ = _ensure_data(values, dtype=dtype)
 
     # faster for larger cases to use np.in1d
@@ -2084,3 +2090,4 @@ def sort_mixed(values):
         np.putmask(new_codes, mask, na_sentinel)
 
     return ordered, ensure_platform_int(new_codes)
+

pandas/tests/frame/methods/test_isin.py

@@ -189,3 +189,17 @@ def test_isin_empty_datetimelike(self):
         tm.assert_frame_equal(result, expected)
         result = df1_td.isin(df3)
         tm.assert_frame_equal(result, expected)
+    
+    def test_isin_int_df_string_search(self):
+        #Comparing df with int`s with a string at isin() -> should not match values
+        df = pd.DataFrame({"values": [1,2]})
+        result = df.isin(["1"])
+        expected_false = pd.DataFrame({"values": [False, False]})
+        tm.assert_frame_equal(result, expected_false)
+
+        #Comparing df with int`s with a int at isin() -> should find the value
+        result = df.isin([1])
+        expected_true = pd.DataFrame({"values": [True, False]})
+        tm.assert_frame_equal(result, expected_true)
+
+