DOC/CLN for GH7213/GH7206

doc/source/timeseries.rst

@@ -413,7 +413,7 @@ regularity will result in a ``DatetimeIndex`` (but frequency is lost):
 Time/Date Components
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-There are several time/date properties that one can access from ``Timestamp`` or a collection of timestamps like a ``DateTimeIndex``. 
+There are several time/date properties that one can access from ``Timestamp`` or a collection of timestamps like a ``DateTimeIndex``.
 
 .. csv-table::
     :header: "Property", "Description"
@@ -604,7 +604,7 @@ in the usual way.
     # Skip new years
     dt = datetime(2013, 12, 17)
     dt + bmth_us
-   
+
     # Define date index with custom offset
     from pandas import DatetimeIndex
     DatetimeIndex(start='20100101',end='20120101',freq=bmth_us)
@@ -789,8 +789,8 @@ methods to return a list of holidays and only ``rules`` need to be defined
 in a specific holiday calendar class.  Further, ``start_date`` and ``end_date``
 class attributes determine over what date range holidays are generated.  These
 should be overwritten on the ``AbstractHolidayCalendar`` class to have the range
-apply to all calendar subclasses.  ``USFederalHolidayCalendar`` is the 
-only calendar that exists and primarily serves as an example for developing 
+apply to all calendar subclasses.  ``USFederalHolidayCalendar`` is the
+only calendar that exists and primarily serves as an example for developing
 other calendars.
 
 For holidays that occur on fixed dates (e.g., US Memorial Day or July 4th) an
@@ -823,12 +823,12 @@ An example of how holidays and holiday calendars are defined:
     cal = ExampleCalendar()
     cal.holidays(datetime(2012, 1, 1), datetime(2012, 12, 31))
 
-Using this calendar, creating an index or doing offset arithmetic skips weekends 
+Using this calendar, creating an index or doing offset arithmetic skips weekends
 and holidays (i.e., Memorial Day/July 4th).
 
 .. ipython:: python
 
-    DatetimeIndex(start='7/1/2012', end='7/10/2012', 
+    DatetimeIndex(start='7/1/2012', end='7/10/2012',
         freq=CDay(calendar=cal)).to_pydatetime()
     offset = CustomBusinessDay(calendar=cal)
     datetime(2012, 5, 25) + offset
@@ -840,11 +840,11 @@ Ranges are defined by the ``start_date`` and ``end_date`` class attributes
 of ``AbstractHolidayCalendar``.  The defaults are below.
 
 .. ipython:: python
-    
+
     AbstractHolidayCalendar.start_date
     AbstractHolidayCalendar.end_date
 
-These dates can be overwritten by setting the attributes as 
+These dates can be overwritten by setting the attributes as
 datetime/Timestamp/string.
 
 .. ipython:: python
@@ -1120,7 +1120,7 @@ Passing string represents lower frequency than `PeriodIndex` returns partial sli
    dfp
    dfp['2013-01-01 10H']
 
-As the same as `DatetimeIndex`, the endpoints will be included in the result. Below example slices data starting from 10:00 to 11:59. 
+As the same as `DatetimeIndex`, the endpoints will be included in the result. Below example slices data starting from 10:00 to 11:59.
 
 .. ipython:: python
 

pandas/core/base.py

@@ -201,16 +201,6 @@ def __unicode__(self):
         return "%s(%s, dtype='%s')" % (type(self).__name__, prepr, self.dtype)
 
 
-# facilitate the properties on the wrapped ops
-def _field_accessor(name, docstring=None):
-    op_accessor = '_{0}'.format(name)
-    def f(self):
-        return self._ops_compat(name,op_accessor)
-
-    f.__name__ = name
-    f.__doc__ = docstring
-    return property(f)
-
 class IndexOpsMixin(object):
     """ common ops mixin to support a unified inteface / docs for Series / Index """
 
@@ -219,24 +209,9 @@ def _is_allowed_index_op(self, name):
             raise TypeError("cannot perform an {name} operations on this type {typ}".format(
                 name=name,typ=type(self._get_access_object())))
 
-    def _is_allowed_datetime_index_op(self, name):
-        if not self._allow_datetime_index_ops:
-            raise TypeError("cannot perform an {name} operations on this type {typ}".format(
-                name=name,typ=type(self._get_access_object())))
-
-    def _is_allowed_period_index_op(self, name):
-        if not self._allow_period_index_ops:
-            raise TypeError("cannot perform an {name} operations on this type {typ}".format(
-                name=name,typ=type(self._get_access_object())))
-
     def _ops_compat(self, name, op_accessor):
-        from pandas.tseries.index import DatetimeIndex
-        from pandas.tseries.period import PeriodIndex
+
         obj = self._get_access_object()
-        if isinstance(obj, DatetimeIndex):
-            self._is_allowed_datetime_index_op(name)
-        elif isinstance(obj, PeriodIndex):
-            self._is_allowed_period_index_op(name)
         try:
             return self._wrap_access_object(getattr(obj,op_accessor))
         except AttributeError:
@@ -336,6 +311,44 @@ def factorize(self, sort=False, na_sentinel=-1):
         from pandas.core.algorithms import factorize
         return factorize(self, sort=sort, na_sentinel=na_sentinel)
 
+# facilitate the properties on the wrapped ops
+def _field_accessor(name, docstring=None):
+    op_accessor = '_{0}'.format(name)
+    def f(self):
+        return self._ops_compat(name,op_accessor)
+
+    f.__name__ = name
+    f.__doc__ = docstring
+    return property(f)
+
+class DatetimeIndexOpsMixin(object):
+    """ common ops mixin to support a unified inteface datetimelike Index """
+
+    def _is_allowed_datetime_index_op(self, name):
+        if not self._allow_datetime_index_ops:
+            raise TypeError("cannot perform an {name} operations on this type {typ}".format(
+                name=name,typ=type(self._get_access_object())))
+
+    def _is_allowed_period_index_op(self, name):
+        if not self._allow_period_index_ops:
+            raise TypeError("cannot perform an {name} operations on this type {typ}".format(
+                name=name,typ=type(self._get_access_object())))
+
+    def _ops_compat(self, name, op_accessor):
+
+        from pandas.tseries.index import DatetimeIndex
+        from pandas.tseries.period import PeriodIndex
+        obj = self._get_access_object()
+        if isinstance(obj, DatetimeIndex):
+            self._is_allowed_datetime_index_op(name)
+        elif isinstance(obj, PeriodIndex):
+            self._is_allowed_period_index_op(name)
+        try:
+            return self._wrap_access_object(getattr(obj,op_accessor))
+        except AttributeError:
+            raise TypeError("cannot perform an {name} operations on this type {typ}".format(
+                name=name,typ=type(obj)))
+
     date = _field_accessor('date','Returns numpy array of datetime.date. The date part of the Timestamps')
     time = _field_accessor('time','Returns numpy array of datetime.time. The time part of the Timestamps')
     year = _field_accessor('year', "The year of the datetime")

pandas/tests/test_base.py

@@ -4,7 +4,7 @@
 import pandas.compat as compat
 import pandas as pd
 from pandas.compat import u, StringIO
-from pandas.core.base import FrozenList, FrozenNDArray
+from pandas.core.base import FrozenList, FrozenNDArray, DatetimeIndexOpsMixin
 from pandas.util.testing import assertRaisesRegexp, assert_isinstance
 from pandas import Series, Index, Int64Index, DatetimeIndex, PeriodIndex
 from pandas import _np_version_under1p7
@@ -181,7 +181,13 @@ def check_ops_properties(self, props, filter=None, ignore_failures=False):
             # we mostly care about Series hwere anyhow
             if not ignore_failures:
                 for o in self.not_valid_objs:
-                    self.assertRaises(TypeError, lambda : getattr(o,op))
+
+                    # an object that is datetimelike will raise a TypeError, otherwise
+                    # an AttributeError
+                    if issubclass(type(o), DatetimeIndexOpsMixin):
+                        self.assertRaises(TypeError, lambda : getattr(o,op))
+                    else:
+                        self.assertRaises(AttributeError, lambda : getattr(o,op))
 
 class TestIndexOps(Ops):
 
@@ -462,6 +468,13 @@ def test_ops_properties_basic(self):
         for op in ['year','day','second','weekday']:
             self.assertRaises(TypeError, lambda x: getattr(self.dt_series,op))
 
+        # attribute access should still work!
+        s = Series(dict(year=2000,month=1,day=10))
+        self.assertEquals(s.year,2000)
+        self.assertEquals(s.month,1)
+        self.assertEquals(s.day,10)
+        self.assertRaises(AttributeError, lambda : s.weekday)
+
 class TestPeriodIndexOps(Ops):
     _allowed = '_allow_period_index_ops'
 

pandas/tests/test_series.py

@@ -5617,12 +5617,6 @@ def test_asfreq(self):
         self.assertEqual(len(result), 0)
         self.assertIsNot(result, ts)
 
-    def test_weekday(self):
-        # Just run the function
-        def f():
-            self.ts.weekday
-        self.assertRaises(TypeError, f)
-
     def test_diff(self):
         # Just run the function
         self.ts.diff()

pandas/tseries/index.py

@@ -15,6 +15,7 @@
 from pandas.tseries.frequencies import (
     infer_freq, to_offset, get_period_alias,
     Resolution, get_reso_string, get_offset)
+from pandas.core.base import DatetimeIndexOpsMixin
 from pandas.tseries.offsets import DateOffset, generate_range, Tick, CDay
 from pandas.tseries.tools import parse_time_string, normalize_date
 from pandas.util.decorators import cache_readonly
@@ -102,7 +103,7 @@ def _ensure_datetime64(other):
 
 _midnight = time(0, 0)
 
-class DatetimeIndex(Int64Index):
+class DatetimeIndex(DatetimeIndexOpsMixin, Int64Index):
     """
     Immutable ndarray of datetime64 data, represented internally as int64, and
     which can be boxed to Timestamp objects that are subclasses of datetime and

pandas/tseries/period.py

@@ -8,6 +8,7 @@
 from pandas.tseries.frequencies import (get_freq_code as _gfc,
                                         _month_numbers, FreqGroup)
 from pandas.tseries.index import DatetimeIndex, Int64Index, Index
+from pandas.core.base import DatetimeIndexOpsMixin
 from pandas.tseries.tools import parse_time_string
 import pandas.tseries.frequencies as _freq_mod
 
@@ -500,7 +501,7 @@ def wrapper(self, other):
     return wrapper
 
 
-class PeriodIndex(Int64Index):
+class PeriodIndex(DatetimeIndexOpsMixin, Int64Index):
     """
     Immutable ndarray holding ordinal values indicating regular periods in
     time such as particular years, quarters, months, etc. A value of 1 is the