Merge branch 'issue-36596' of https://github.com/OlehKSS/pandas into issue-36596

Author: Oleh Kozynets

doc/source/whatsnew/v1.2.0.rst

@@ -434,6 +434,7 @@ Numeric
 - Bug in :class:`DataFrame` allowing arithmetic operations with list of array-likes with undefined results. Behavior changed to raising ``ValueError`` (:issue:`36702`)
 - Bug in :meth:`DataFrame.std`` with ``timedelta64`` dtype and ``skipna=False`` (:issue:`37392`)
 - Bug in :meth:`DataFrame.min` and :meth:`DataFrame.max` with ``datetime64`` dtype and ``skipna=False`` (:issue:`36907`)
+- Bug in :func:`select_dtypes` different behavior between Windows and Linux with ``include="int"`` (:issue:`36569`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/dtypes/common.py

@@ -1796,6 +1796,11 @@ def pandas_dtype(dtype) -> DtypeObj:
     # try a numpy dtype
     # raise a consistent TypeError if failed
     try:
+        # int is mapped to different types (int32, in64) on Windows and Linux
+        # see https://github.com/numpy/numpy/issues/9464
+        if (isinstance(dtype, str) and dtype == "int") or (dtype is int):
+            dtype = "int64"
+
         npdtype = np.dtype(dtype)
     except SyntaxError as err:
         # np.dtype uses `eval` which can raise SyntaxError

pandas/tests/dtypes/test_common.py

@@ -43,20 +43,22 @@ def test_invalid_dtype_error(self, box):
             com.pandas_dtype(box)
 
     @pytest.mark.parametrize(
-        "dtype",
+        "dtype_input,dtype_output",
         [
-            object,
-            "float64",
-            np.object_,
-            np.dtype("object"),
-            "O",
-            np.float64,
-            float,
-            np.dtype("float64"),
+            (object, object),
+            ("float64", np.float64),
+            (np.object_, np.object_),
+            (np.dtype("object"), np.object_),
+            ("O", object),
+            (np.float64, np.float64),
+            (float, float),
+            (np.dtype("float64"), np.float64),
+            ("int", np.int64),
+            (int, np.int64),
         ],
     )
-    def test_pandas_dtype_valid(self, dtype):
-        assert com.pandas_dtype(dtype) == dtype
+    def test_pandas_dtype_valid(self, dtype_input, dtype_output):
+        assert com.pandas_dtype(dtype_input) == dtype_output
 
     @pytest.mark.parametrize(
         "dtype", ["M8[ns]", "m8[ns]", "object", "float64", "int64"]

pandas/tests/frame/methods/test_select_dtypes.py

@@ -82,6 +82,12 @@ def test_select_dtypes_exclude_include_using_list_like(self):
         e = df[["b", "c", "e"]]
         tm.assert_frame_equal(r, e)
 
+        exclude = (np.datetime64,)
+        include = np.bool_, "int"
+        r = df.select_dtypes(include=include, exclude=exclude)
+        e = df[["b", "e"]]
+        tm.assert_frame_equal(r, e)
+
         exclude = ("datetime",)
         include = "bool", "int64", "int32"
         r = df.select_dtypes(include=include, exclude=exclude)