API: NaT boolean accessors

TST: add pandas/tests/scalar/test_nat

TST: revise testing of tseries accessors

closes pandas-dev#15781

doc/source/whatsnew/v0.20.0.txt

@@ -729,6 +729,8 @@ Other API Changes
 - ``Series.sort_values()`` accepts a one element list of bool for consistency with the behavior of ``DataFrame.sort_values()`` (:issue:`15604`)
 - ``.merge()`` and ``.join()`` on ``category`` dtype columns will now preserve the category dtype when possible (:issue:`10409`)
 - ``SparseDataFrame.default_fill_value`` will be 0, previously was ``nan`` in the return from ``pd.get_dummies(..., sparse=True)`` (:issue:`15594`)
+- ``NaT`` will now correctly report ``False`` for datetimelike boolean operations such as ``is_month_start`` (:issue:`15781`)
+- ``NaT`` will now correctly return ``np.nan`` for ``Timedelta`` and ``Period`` accessors such as ``days`` and ``quarter`` (:issue:`15782`)
 
 .. _whatsnew_0200.deprecations:
 
@@ -936,4 +938,3 @@ Bug Fixes
 - Bug in ``pd.melt()`` where passing a tuple value for ``value_vars`` caused a ``TypeError`` (:issue:`15348`)
 - Bug in ``.eval()`` which caused multiline evals to fail with local variables not on the first line (:issue:`15342`)
 - Bug in ``pd.read_msgpack`` which did not allow to load dataframe with an index of type ``CategoricalIndex`` (:issue:`15487`)
-

pandas/_libs/tslib.pyx

@@ -849,6 +849,30 @@ class NaTType(_NaT):
     def is_leap_year(self):
         return False
 
+    @property
+    def is_month_start(self):
+        return False
+
+    @property
+    def is_quarter_start(self):
+        return False
+
+    @property
+    def is_year_start(self):
+        return False
+
+    @property
+    def is_month_end(self):
+        return False
+
+    @property
+    def is_quarter_end(self):
+        return False
+
+    @property
+    def is_year_end(self):
+        return False
+
     def __rdiv__(self, other):
         return _nat_rdivide_op(self, other)
 
@@ -3799,8 +3823,9 @@ def array_strptime(ndarray[object] values, object fmt,
 # these by definition return np.nan
 fields = ['year', 'quarter', 'month', 'day', 'hour',
           'minute', 'second', 'millisecond', 'microsecond', 'nanosecond',
-          'week', 'dayofyear', 'days_in_month', 'daysinmonth', 'dayofweek',
-          'weekday_name']
+          'week', 'dayofyear', 'weekofyear', 'days_in_month', 'daysinmonth',
+          'dayofweek', 'weekday_name', 'days', 'seconds', 'microseconds',
+          'nanoseconds', 'qyear', 'quarter']
 for field in fields:
     prop = property(fget=lambda self: np.nan)
     setattr(NaTType, field, prop)
@@ -4810,7 +4835,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
     if field == 'is_month_start':
         if is_business:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4823,7 +4848,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
             return out.view(bool)
         else:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4836,7 +4861,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
     elif field == 'is_month_end':
         if is_business:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4854,7 +4879,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
             return out.view(bool)
         else:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4871,7 +4896,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
     elif field == 'is_quarter_start':
         if is_business:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4885,7 +4910,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
             return out.view(bool)
         else:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4898,7 +4923,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
     elif field == 'is_quarter_end':
         if is_business:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4917,7 +4942,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
             return out.view(bool)
         else:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4934,7 +4959,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
     elif field == 'is_year_start':
         if is_business:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4948,7 +4973,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
             return out.view(bool)
         else:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4961,7 +4986,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
     elif field == 'is_year_end':
         if is_business:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)
@@ -4980,7 +5005,7 @@ def get_start_end_field(ndarray[int64_t] dtindex, object field,
             return out.view(bool)
         else:
             for i in range(count):
-                if dtindex[i] == NPY_NAT: out[i] = -1; continue
+                if dtindex[i] == NPY_NAT: out[i] = 0; continue
 
                 pandas_datetime_to_datetimestruct(
                     dtindex[i], PANDAS_FR_ns, &dts)

pandas/tests/indexes/datetimes/test_ops.py

@@ -31,15 +31,10 @@ def setUp(self):
         self.not_valid_objs = [o for o in self.objs if not mask(o)]
 
     def test_ops_properties(self):
-        self.check_ops_properties(
-            ['year', 'month', 'day', 'hour', 'minute', 'second', 'weekofyear',
-             'week', 'dayofweek', 'dayofyear', 'quarter'])
-        self.check_ops_properties(['date', 'time', 'microsecond', 'nanosecond',
-                                   'is_month_start', 'is_month_end',
-                                   'is_quarter_start',
-                                   'is_quarter_end', 'is_year_start',
-                                   'is_year_end', 'weekday_name'],
-                                  lambda x: isinstance(x, DatetimeIndex))
+        f = lambda x: isinstance(x, DatetimeIndex)
+        self.check_ops_properties(DatetimeIndex._field_ops, f)
+        self.check_ops_properties(DatetimeIndex._object_ops, f)
+        self.check_ops_properties(DatetimeIndex._bool_ops, f)
 
     def test_ops_properties_basic(self):
 

pandas/tests/indexes/period/test_ops.py

@@ -21,11 +21,10 @@ def setUp(self):
         self.not_valid_objs = [o for o in self.objs if not mask(o)]
 
     def test_ops_properties(self):
-        self.check_ops_properties(
-            ['year', 'month', 'day', 'hour', 'minute', 'second', 'weekofyear',
-             'week', 'dayofweek', 'dayofyear', 'quarter'])
-        self.check_ops_properties(['qyear'],
-                                  lambda x: isinstance(x, PeriodIndex))
+        f = lambda x: isinstance(x, PeriodIndex)
+        self.check_ops_properties(PeriodIndex._field_ops, f)
+        self.check_ops_properties(PeriodIndex._object_ops, f)
+        self.check_ops_properties(PeriodIndex._bool_ops, f)
 
     def test_asobject_tolist(self):
         idx = pd.period_range(start='2013-01-01', periods=4, freq='M',

pandas/tests/indexes/period/test_period.py

@@ -394,8 +394,8 @@ def test_fields(self):
 
     def _check_all_fields(self, periodindex):
         fields = ['year', 'month', 'day', 'hour', 'minute', 'second',
-                  'weekofyear', 'week', 'dayofweek', 'weekday', 'dayofyear',
-                  'quarter', 'qyear', 'days_in_month', 'is_leap_year']
+                  'weekofyear', 'week', 'dayofweek', 'dayofyear',
+                  'quarter', 'qyear', 'days_in_month']
 
         periods = list(periodindex)
         s = pd.Series(periodindex)

pandas/tests/indexes/timedeltas/test_ops.py

@@ -21,9 +21,9 @@ def setUp(self):
         self.not_valid_objs = []
 
     def test_ops_properties(self):
-        self.check_ops_properties(['days', 'hours', 'minutes', 'seconds',
-                                   'milliseconds'])
-        self.check_ops_properties(['microseconds', 'nanoseconds'])
+        f = lambda x: isinstance(x, TimedeltaIndex)
+        self.check_ops_properties(TimedeltaIndex._field_ops, f)
+        self.check_ops_properties(TimedeltaIndex._object_ops, f)
 
     def test_asobject_tolist(self):
         idx = timedelta_range(start='1 days', periods=4, freq='D', name='idx')