Update type for PeriodDtype / DatetimeTZDtype / IntervalDtype (pandas-dev#22938)

Author: TomAugspurger

Diff for: doc/source/whatsnew/v0.24.0.txt

@@ -505,6 +505,7 @@ ExtensionType Changes
 - :meth:`Series.astype` and :meth:`DataFrame.astype` now dispatch to :meth:`ExtensionArray.astype` (:issue:`21185:`).
 - Slicing a single row of a ``DataFrame`` with multiple ExtensionArrays of the same type now preserves the dtype, rather than coercing to object (:issue:`22784`)
 - Added :meth:`pandas.api.types.register_extension_dtype` to register an extension type with pandas (:issue:`22664`)
+- Updated the ``.type`` attribute for ``PeriodDtype``, ``DatetimeTZDtype``, and ``IntervalDtype`` to be instances of the dtype (``Period``, ``Timestamp``, and ``Interval`` respectively) (:issue:`22938`)
 
 .. _whatsnew_0240.api.incompatibilities:
 

Diff for: pandas/core/dtypes/base.py

@@ -181,7 +181,9 @@ def type(self):
         """The scalar type for the array, e.g. ``int``
 
         It's expected ``ExtensionArray[item]`` returns an instance
-        of ``ExtensionDtype.type`` for scalar ``item``.
+        of ``ExtensionDtype.type`` for scalar ``item``, assuming
+        that value is valid (not NA). NA values do not need to be
+        instances of `type`.
         """
         raise AbstractMethodError(self)
 

Diff for: pandas/core/dtypes/common.py

@@ -4,12 +4,13 @@
 from pandas.compat import (string_types, text_type, binary_type,
                            PY3, PY36)
 from pandas._libs import algos, lib
-from pandas._libs.tslibs import conversion
+from pandas._libs.tslibs import conversion, Period, Timestamp
+from pandas._libs.interval import Interval
 
 from pandas.core.dtypes.dtypes import (
     registry, CategoricalDtype, CategoricalDtypeType, DatetimeTZDtype,
-    DatetimeTZDtypeType, PeriodDtype, PeriodDtypeType, IntervalDtype,
-    IntervalDtypeType, PandasExtensionDtype, ExtensionDtype,
+    PeriodDtype, IntervalDtype,
+    PandasExtensionDtype, ExtensionDtype,
     _pandas_registry)
 from pandas.core.dtypes.generic import (
     ABCCategorical, ABCPeriodIndex, ABCDatetimeIndex, ABCSeries,
@@ -1905,20 +1906,20 @@ def _get_dtype_type(arr_or_dtype):
     elif isinstance(arr_or_dtype, CategoricalDtype):
         return CategoricalDtypeType
     elif isinstance(arr_or_dtype, DatetimeTZDtype):
-        return DatetimeTZDtypeType
+        return Timestamp
     elif isinstance(arr_or_dtype, IntervalDtype):
-        return IntervalDtypeType
+        return Interval
     elif isinstance(arr_or_dtype, PeriodDtype):
-        return PeriodDtypeType
+        return Period
     elif isinstance(arr_or_dtype, string_types):
         if is_categorical_dtype(arr_or_dtype):
             return CategoricalDtypeType
         elif is_datetime64tz_dtype(arr_or_dtype):
-            return DatetimeTZDtypeType
+            return Timestamp
         elif is_period_dtype(arr_or_dtype):
-            return PeriodDtypeType
+            return Period
         elif is_interval_dtype(arr_or_dtype):
-            return IntervalDtypeType
+            return Interval
         return _get_dtype_type(np.dtype(arr_or_dtype))
     try:
         return arr_or_dtype.dtype.type

Diff for: pandas/core/dtypes/dtypes.py

@@ -4,6 +4,8 @@
 import numpy as np
 from pandas import compat
 from pandas.core.dtypes.generic import ABCIndexClass, ABCCategoricalIndex
+from pandas._libs.tslibs import Period, NaT, Timestamp
+from pandas._libs.interval import Interval
 
 from .base import ExtensionDtype, _DtypeOpsMixin
 
@@ -469,13 +471,6 @@ def _is_boolean(self):
         return is_bool_dtype(self.categories)
 
 
-class DatetimeTZDtypeType(type):
-    """
-    the type of DatetimeTZDtype, this metaclass determines subclass ability
-    """
-    pass
-
-
 class DatetimeTZDtype(PandasExtensionDtype):
 
     """
@@ -485,7 +480,7 @@ class DatetimeTZDtype(PandasExtensionDtype):
     THIS IS NOT A REAL NUMPY DTYPE, but essentially a sub-class of
     np.datetime64[ns]
     """
-    type = DatetimeTZDtypeType
+    type = Timestamp
     kind = 'M'
     str = '|M8[ns]'
     num = 101
@@ -583,20 +578,13 @@ def __eq__(self, other):
                 str(self.tz) == str(other.tz))
 
 
-class PeriodDtypeType(type):
-    """
-    the type of PeriodDtype, this metaclass determines subclass ability
-    """
-    pass
-
-
 class PeriodDtype(PandasExtensionDtype):
     """
     A Period duck-typed class, suitable for holding a period with freq dtype.
 
     THIS IS NOT A REAL NUMPY DTYPE, but essentially a sub-class of np.int64.
     """
-    type = PeriodDtypeType
+    type = Period
     kind = 'O'
     str = '|O08'
     base = np.dtype('O')
@@ -666,11 +654,15 @@ def construct_from_string(cls, string):
         raise TypeError("could not construct PeriodDtype")
 
     def __unicode__(self):
-        return "period[{freq}]".format(freq=self.freq.freqstr)
+        return compat.text_type(self.name)
 
     @property
     def name(self):
-        return str(self)
+        return str("period[{freq}]".format(freq=self.freq.freqstr))
+
+    @property
+    def na_value(self):
+        return NaT
 
     def __hash__(self):
         # make myself hashable
@@ -705,13 +697,6 @@ def is_dtype(cls, dtype):
         return super(PeriodDtype, cls).is_dtype(dtype)
 
 
-class IntervalDtypeType(type):
-    """
-    the type of IntervalDtype, this metaclass determines subclass ability
-    """
-    pass
-
-
 @register_extension_dtype
 class IntervalDtype(PandasExtensionDtype, ExtensionDtype):
     """
@@ -800,7 +785,6 @@ def construct_from_string(cls, string):
 
     @property
     def type(self):
-        from pandas import Interval
         return Interval
 
     def __unicode__(self):

Diff for: pandas/tests/dtypes/test_common.py

@@ -605,15 +605,15 @@ def test__get_dtype_fails(input_param):
     (pd.DatetimeIndex([1, 2]), np.datetime64),
     (pd.DatetimeIndex([1, 2]).dtype, np.datetime64),
     ('<M8[ns]', np.datetime64),
-    (pd.DatetimeIndex([1, 2], tz='Europe/London'), com.DatetimeTZDtypeType),
+    (pd.DatetimeIndex([1, 2], tz='Europe/London'), pd.Timestamp),
     (pd.DatetimeIndex([1, 2], tz='Europe/London').dtype,
-     com.DatetimeTZDtypeType),
-    ('datetime64[ns, Europe/London]', com.DatetimeTZDtypeType),
+     pd.Timestamp),
+    ('datetime64[ns, Europe/London]', pd.Timestamp),
     (pd.SparseSeries([1, 2], dtype='int32'), np.int32),
     (pd.SparseSeries([1, 2], dtype='int32').dtype, np.int32),
-    (PeriodDtype(freq='D'), com.PeriodDtypeType),
-    ('period[D]', com.PeriodDtypeType),
-    (IntervalDtype(), com.IntervalDtypeType),
+    (PeriodDtype(freq='D'), pd.Period),
+    ('period[D]', pd.Period),
+    (IntervalDtype(), pd.Interval),
     (None, type(None)),
     (1, type(None)),
     (1.2, type(None)),