Various cleanups

Author: TomAugspurger

pandas/core/arrays/base.py

@@ -1,8 +1,6 @@
 """An interface for extending pandas with custom arrays."""
 import abc
 
-import numpy as np
-
 from pandas.compat import add_metaclass
 
 
@@ -11,7 +9,7 @@
 
 @add_metaclass(abc.ABCMeta)
 class ExtensionArray(object):
-    """Abstract base class for custom array types
+    """Abstract base class for custom array types.
 
     Notes
     -----
@@ -23,6 +21,9 @@ class ExtensionArray(object):
         * Extension arrays should be able to be constructed with instances of
           the class, i.e. ``ExtensionArray(extension_array)`` should return
           an instance, not error.
+
+    Additionally, certain methods and interfaces are required for proper
+    this array to be properly stored inside a ``DataFrame`` or ``Series``.
     """
     # ------------------------------------------------------------------------
     # Must be a Sequence

pandas/core/arrays/categorical.py

@@ -2132,8 +2132,7 @@ def repeat(self, repeats, *args, **kwargs):
         return self._constructor(values=codes, categories=self.categories,
                                  ordered=self.ordered, fastpath=True)
 
-    # Interface things
-    # can_hold_na, concat_same_type, formatting_values
+    # ExtensionArray Interface things
     @property
     def _can_hold_na(self):
         return True

pandas/core/dtypes/base.py

@@ -6,7 +6,7 @@
 
 @add_metaclass(abc.ABCMeta)
 class ExtensionDtype(object):
-    """A custom data type for your array.
+    """A custom data type, to be paired with an ExtensionArray.
     """
 
     def __str__(self):
@@ -16,7 +16,7 @@ def __str__(self):
     @abc.abstractmethod
     def type(self):
         # type: () -> type
-        """The scalar type for your array, e.g. ``int``
+        """The scalar type for the array, e.g. ``int``
 
         It's expected ``ExtensionArray[item]`` returns an instance
         of ``ExtensionDtype.type`` for scalar ``item``.
@@ -27,9 +27,9 @@ def kind(self):
         # type () -> str
         """A character code (one of 'biufcmMOSUV'), default 'O'
 
-        This should match the NumPy dtype used when your array is
+        This should match the NumPy dtype used when the array is
         converted to an ndarray, which is probably 'O' for object if
-        your extension type cannot be represented as a built-in NumPy
+        the extension type cannot be represented as a built-in NumPy
         type.
 
         See Also
@@ -71,11 +71,6 @@ def construct_from_string(cls, string):
         TypeError
             If a class cannot be constructed from this 'string'.
 
-        Notes
-        -----
-        The default implementation checks if 'string' matches your
-        type's name. If so, it calls your class with no arguments.
-
         Examples
         --------
         If the extension dtype can be constructed without any arguments,

pandas/core/dtypes/common.py

@@ -1686,7 +1686,7 @@ def is_extension_type(arr):
 
 
 def is_extension_array_dtype(arr_or_dtype):
-    """Check if an object is a pandas extension array type
+    """Check if an object is a pandas extension array type.
 
     Parameters
     ----------
@@ -1702,9 +1702,6 @@ def is_extension_array_dtype(arr_or_dtype):
     array interface. In pandas, this includes:
 
     * Categorical
-    * PeriodArray
-    * IntervalArray
-    * SparseArray
 
     Third-party libraries may implement arrays or types satisfying
     this interface as well.

pandas/core/internals.py

@@ -1848,13 +1848,8 @@ def take_nd(self, indexer, axis=0, new_mgr_locs=None, fill_tuple=None):
         return self.make_block_same_class(new_values, new_mgr_locs)
 
     def _can_hold_element(self, element):
-        # XXX:
-        # Not defined on NCM.
-        # Categorical got True from ObjectBlock
-        # DatetimeTZ gets DatetimeBlock
-        # Sparse gets Block
-        # Let's just assume yes for now, but we can maybe push
-        # this onto the array.
+        # XXX: We may need to think about pushing this onto the array.
+        # We're doing the same as CategoricalBlock here.
         return True
 
     def convert(self, copy=True, **kwargs):