Update type for PeriodDtype

Removed unused IntervalDtypeType

Author: TomAugspurger

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
+from pandas._libs.interval import Interval
 
 from pandas.core.dtypes.dtypes import (
     registry, CategoricalDtype, CategoricalDtypeType, DatetimeTZDtype,
-    DatetimeTZDtypeType, PeriodDtype, PeriodDtypeType, IntervalDtype,
-    IntervalDtypeType, PandasExtensionDtype, ExtensionDtype,
+    DatetimeTZDtypeType, PeriodDtype, IntervalDtype,
+    PandasExtensionDtype, ExtensionDtype,
     _pandas_registry)
 from pandas.core.dtypes.generic import (
     ABCCategorical, ABCPeriodIndex, ABCDatetimeIndex, ABCSeries,
@@ -1907,18 +1908,18 @@ def _get_dtype_type(arr_or_dtype):
     elif isinstance(arr_or_dtype, DatetimeTZDtype):
         return DatetimeTZDtypeType
     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
         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 +4,7 @@
 import numpy as np
 from pandas import compat
 from pandas.core.dtypes.generic import ABCIndexClass, ABCCategoricalIndex
+from pandas._libs.tslibs import Period, NaT
 
 from .base import ExtensionDtype, _DtypeOpsMixin
 
@@ -583,20 +584,13 @@ 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 +660,15 @@ def construct_from_string(cls, string):
         raise TypeError("could not construct PeriodDtype")
 
     def __unicode__(self):
-        return "period[{freq}]".format(freq=self.freq.freqstr)
+        return self.name
 
     @property
     def name(self):
-        return str(self)
+        return u"period[{freq}]".format(freq=self.freq.freqstr)
+
+    @property
+    def na_value(self):
+        return NaT
 
     def __hash__(self):
         # make myself hashable
@@ -705,13 +703,6 @@ 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):
     """

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

@@ -611,9 +611,9 @@ def test__get_dtype_fails(input_param):
     ('datetime64[ns, Europe/London]', com.DatetimeTZDtypeType),
     (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)),