ENH: Select numeric ExtensionDtypes with DataFrame.select_dtypes

pandas/compat/numpy/__init__.py

@@ -5,6 +5,8 @@
 
 import numpy as np
 
+from pandas.core.dtypes.common import is_extension_array_dtype
+
 # numpy versioning
 _np_version = np.__version__
 _nlv = LooseVersion(_np_version)
@@ -62,6 +64,16 @@ def np_array_datetime64_compat(arr, *args, **kwargs):
     return np.array(arr, *args, **kwargs)
 
 
+def np_issubclass_compat(unique_dtype, dtypes_set):
+    if (issubclass(unique_dtype.type, tuple(dtypes_set))  # type: ignore
+        or (
+            np.number in dtypes_set
+            and is_extension_array_dtype(unique_dtype)
+            and unique_dtype._is_numeric
+    )):
+        return True
+    return False
+
 __all__ = [
     "np",
     "_np_version",

pandas/core/frame.py

@@ -60,6 +60,7 @@
 from pandas.compat import PY37
 from pandas.compat._optional import import_optional_dependency
 from pandas.compat.numpy import function as nv
+from pandas.compat.numpy import np_issubclass_compat
 from pandas.util._decorators import (
     Appender,
     Substitution,
@@ -3547,6 +3548,7 @@ def select_dtypes(self, include=None, exclude=None) -> "DataFrame":
         4   True  1.0
         5  False  2.0
         """
+
         if not is_list_like(include):
             include = (include,) if include is not None else ()
         if not is_list_like(exclude):
@@ -3577,7 +3579,7 @@ def extract_unique_dtypes_from_dtypes_set(
             extracted_dtypes = [
                 unique_dtype
                 for unique_dtype in unique_dtypes
-                if issubclass(unique_dtype.type, tuple(dtypes_set))  # type: ignore
+                if np_issubclass_compat(unique_dtype, dtypes_set)
             ]
             return extracted_dtypes
 

pandas/tests/extension/test_select_dtypes_numeric.py

@@ -0,0 +1,51 @@
+import pytest
+import numpy as np
+
+import pandas as pd
+from pandas.core.arrays import ExtensionArray
+from pandas.core.dtypes.dtypes import ExtensionDtype
+
+
+class DummyDtype(ExtensionDtype):
+    type = int
+    _numeric = False
+
+    @property
+    def name(self):
+        return "Dummy"
+
+    @property
+    def _is_numeric(self):
+        return self._numeric
+
+
+class DummyArray(ExtensionArray):
+    _dtype = DummyDtype()
+
+    def __init__(self, data):
+        self.data = data
+
+    def __array__(self, dtype):
+        return self.data
+
+    @property
+    def dtype(self):
+        return self._dtype
+
+    def __len__(self) -> int:
+        return len(self.data)
+
+    def __getitem__(self, item):
+        pass
+
+
+def test_select_dtypes_numeric():
+    da = DummyArray([1, 2])
+    da._dtype._numeric = True
+    df = pd.DataFrame(da)
+    assert df.select_dtypes(np.number).shape == df.shape
+
+    da = DummyArray([1, 2])
+    da._dtype._numeric = False
+    df = pd.DataFrame(da)
+    assert df.select_dtypes(np.number).shape != df.shape