diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
index ce87c0a8b0c5a..30949ca6d1d6b 100644
--- a/pandas/core/arrays/base.py
+++ b/pandas/core/arrays/base.py
@@ -195,13 +195,13 @@ def __setitem__(self, key, value):
         )
 
     def __len__(self):
+        # type: () -> int
         """Length of this array
 
         Returns
         -------
         length : int
         """
-        # type: () -> int
         raise AbstractMethodError(self)
 
     def __iter__(self):
diff --git a/pandas/core/base.py b/pandas/core/base.py
index c331ead8d2fef..6625a3bbe97d7 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -788,6 +788,7 @@ def base(self):
 
     @property
     def _ndarray_values(self):
+        # type: () -> np.ndarray
         """The data as an ndarray, possibly losing information.
 
         The expectation is that this is cheap to compute, and is primarily
@@ -795,7 +796,6 @@ def _ndarray_values(self):
 
         - categorical -> codes
         """
-        # type: () -> np.ndarray
         if is_extension_array_dtype(self):
             return self.values._ndarray_values
         return self.values
diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index c45838e6040a9..05f82c67ddb8b 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -5,17 +5,19 @@
                            PY3, PY36)
 from pandas._libs import algos, lib
 from pandas._libs.tslibs import conversion
-from .dtypes import (CategoricalDtype, CategoricalDtypeType,
-                     DatetimeTZDtype, DatetimeTZDtypeType,
-                     PeriodDtype, PeriodDtypeType,
-                     IntervalDtype, IntervalDtypeType,
-                     ExtensionDtype, PandasExtensionDtype)
-from .generic import (ABCCategorical, ABCPeriodIndex,
-                      ABCDatetimeIndex, ABCSeries,
-                      ABCSparseArray, ABCSparseSeries, ABCCategoricalIndex,
-                      ABCIndexClass, ABCDateOffset)
-from .inference import is_string_like, is_list_like
-from .inference import *  # noqa
+from pandas.core.dtypes.dtypes import (
+    CategoricalDtype, CategoricalDtypeType, DatetimeTZDtype,
+    DatetimeTZDtypeType, PeriodDtype, PeriodDtypeType, IntervalDtype,
+    IntervalDtypeType, ExtensionDtype, PandasExtensionDtype)
+from pandas.core.dtypes.generic import (
+    ABCCategorical, ABCPeriodIndex, ABCDatetimeIndex, ABCSeries,
+    ABCSparseArray, ABCSparseSeries, ABCCategoricalIndex, ABCIndexClass,
+    ABCDateOffset)
+from pandas.core.dtypes.inference import (  # noqa:F401
+    is_bool, is_integer, is_hashable, is_iterator, is_float,
+    is_dict_like, is_scalar, is_string_like, is_list_like, is_number,
+    is_file_like, is_re, is_re_compilable, is_sequence, is_nested_list_like,
+    is_named_tuple, is_array_like, is_decimal, is_complex, is_interval)
 
 
 _POSSIBLY_CAST_DTYPES = set([np.dtype(t).name