ENH: rounding for datetimelike Indexes/Scalars

doc/source/api.rst

@@ -526,6 +526,7 @@ These can be accessed like ``Series.dt.<property>``.
    Series.dt.tz_convert
    Series.dt.normalize
    Series.dt.strftime
+   Series.dt.round
 
 **Timedelta Properties**
 
@@ -1507,7 +1508,7 @@ Time-specific operations
    DatetimeIndex.snap
    DatetimeIndex.tz_convert
    DatetimeIndex.tz_localize
-
+   DatetimeIndex.round
 
 Conversion
 ~~~~~~~~~~
@@ -1548,6 +1549,7 @@ Conversion
 
    TimedeltaIndex.to_pytimedelta
    TimedeltaIndex.to_series
+   TimedeltaIndex.round
 
 GroupBy
 -------

doc/source/whatsnew/v0.18.0.txt

@@ -31,13 +31,53 @@ New features
 Other enhancements
 ^^^^^^^^^^^^^^^^^^
 
+.. _whatsnew_0180.enhancements.rounding:
 
+Datetimelike rounding
+^^^^^^^^^^^^^^^^^^^^^
 
+``DatetimeIndex``, ``Timestamp``, ``TimedeltaIndex``, ``Timedelta`` have gained the ``.round()`` method for datetimelike rounding. (:issue:`4314`)
 
+Naive datetimes
 
+.. ipython:: python
 
+   dr = pd.date_range('20130101 09:12:56.1234', periods=3)
+   dr
+   dr.round('s')
 
+   # Timestamp scalar
+   dr[0]
+   dr[0].round('10s')
 
+Tz-aware are rounded in local times
+
+.. ipython:: python
+
+   dr = dr.tz_localize('US/Eastern')
+   dr
+   dr.round('s')
+
+Timedeltas
+
+.. ipython:: python
+
+   t = timedelta_range('1 days 2 hr 13 min 45 us',periods=3,freq='d')
+   t
+   t.round('10min')
+
+   # Timedelta scalar
+   t[0]
+   t[0].round('2h')
+
+
+In addition, ``.round()`` will be available thru the ``.dt`` accessor of ``Series``.
+
+.. ipython:: python
+
+   s = Series(dr)
+   s
+   s.dt.round('D')
 
 .. _whatsnew_0180.api:
 
@@ -65,6 +105,9 @@ Other API Changes
 
 
 
+
+
+
 .. _whatsnew_0180.deprecations:
 
 Deprecations
@@ -107,5 +150,5 @@ Bug Fixes
 ~~~~~~~~~
 
 
-
+- Bug in ``Timedelta.round`` with negative values (:issue:`11690`)
 - Bug in ``.loc`` against ``CategoricalIndex`` may result in normal ``Index`` (:issue:`11586`)

pandas/tests/test_categorical.py

@@ -3753,6 +3753,7 @@ def test_dt_accessor_api_for_categorical(self):
         special_func_defs = [
             ('strftime', ("%Y-%m-%d",), {}),
             ('tz_convert', ("EST",), {}),
+            ('round', ("D",), {}),
             #('tz_localize', ("UTC",), {}),
         ]
         _special_func_names = [f[0] for f in special_func_defs]

pandas/tests/test_series.py

@@ -88,9 +88,9 @@ def test_dt_namespace_accessor(self):
         ok_for_period_methods = ['strftime']
         ok_for_dt = ok_for_base + ['date','time','microsecond','nanosecond', 'is_month_start', 'is_month_end', 'is_quarter_start',
                                    'is_quarter_end', 'is_year_start', 'is_year_end', 'tz']
-        ok_for_dt_methods = ['to_period','to_pydatetime','tz_localize','tz_convert', 'normalize', 'strftime']
+        ok_for_dt_methods = ['to_period','to_pydatetime','tz_localize','tz_convert', 'normalize', 'strftime', 'round']
         ok_for_td = ['days','seconds','microseconds','nanoseconds']
-        ok_for_td_methods = ['components','to_pytimedelta','total_seconds']
+        ok_for_td_methods = ['components','to_pytimedelta','total_seconds','round']
 
         def get_expected(s, name):
             result = getattr(Index(s._values),prop)
@@ -139,6 +139,17 @@ def compare(s, name):
             expected = Series(DatetimeIndex(s.values).tz_localize('UTC').tz_convert('US/Eastern'),index=s.index)
             tm.assert_series_equal(result, expected)
 
+        # round
+        s = Series(date_range('20130101 09:10:11',periods=5))
+        result = s.dt.round('D')
+        expected = Series(date_range('20130101',periods=5))
+        tm.assert_series_equal(result, expected)
+
+        # round with tz
+        result = s.dt.tz_localize('UTC').dt.tz_convert('US/Eastern').dt.round('D')
+        expected = Series(date_range('20130101',periods=5)).dt.tz_localize('US/Eastern')
+        tm.assert_series_equal(result, expected)
+
         # datetimeindex with tz
         s = Series(date_range('20130101',periods=5,tz='US/Eastern'))
         for prop in ok_for_dt:

pandas/tseries/base.py

@@ -41,6 +41,46 @@ def strftime(self, date_format):
         """
         return np.asarray(self.format(date_format=date_format))
 
+class TimelikeOps(object):
+    """ common ops for TimedeltaIndex/DatetimeIndex, but not PeriodIndex """
+
+    def round(self, freq):
+        """
+        Round the index to the specified freq; this is a floor type of operation
+
+        Paramaters
+        ----------
+        freq : freq string/object
+
+        Returns
+        -------
+        index of same type
+
+        Raises
+        ------
+        ValueError if the freq cannot be converted
+        """
+
+        from pandas.tseries.frequencies import to_offset
+        unit = to_offset(freq).nanos
+
+        # round the local times
+        if getattr(self,'tz',None) is not None:
+            values = self.tz_localize(None).asi8
+        else:
+            values = self.asi8
+        result = (unit*np.floor(values/unit)).astype('i8')
+        attribs = self._get_attributes_dict()
+        if 'freq' in attribs:
+            attribs['freq'] = None
+        if 'tz' in attribs:
+            attribs['tz'] = None
+        result = self._shallow_copy(result, **attribs)
+
+        # reconvert to local tz
+        if getattr(self,'tz',None) is not None:
+            result = result.tz_localize(self.tz)
+        return result
 
 class DatetimeIndexOpsMixin(object):
     """ common ops mixin to support a unified inteface datetimelike Index """

pandas/tseries/common.py

@@ -145,7 +145,8 @@ def to_pydatetime(self):
                                            accessors=DatetimeIndex._datetimelike_ops,
                                            typ='property')
 DatetimeProperties._add_delegate_accessors(delegate=DatetimeIndex,
-                                           accessors=["to_period","tz_localize","tz_convert","normalize","strftime"],
+                                           accessors=["to_period","tz_localize","tz_convert",
+                                                      "normalize","strftime","round"],
                                            typ='method')
 
 class TimedeltaProperties(Properties):
@@ -181,7 +182,7 @@ def components(self):
                                             accessors=TimedeltaIndex._datetimelike_ops,
                                             typ='property')
 TimedeltaProperties._add_delegate_accessors(delegate=TimedeltaIndex,
-                                            accessors=["to_pytimedelta", "total_seconds"],
+                                            accessors=["to_pytimedelta", "total_seconds", "round"],
                                             typ='method')
 
 class PeriodProperties(Properties):

pandas/tseries/index.py

@@ -19,7 +19,7 @@
 from pandas.tseries.frequencies import (
     to_offset, get_period_alias,
     Resolution)
-from pandas.tseries.base import DatelikeOps, DatetimeIndexOpsMixin
+from pandas.tseries.base import DatelikeOps, TimelikeOps, DatetimeIndexOpsMixin
 from pandas.tseries.offsets import DateOffset, generate_range, Tick, CDay
 from pandas.tseries.tools import parse_time_string, normalize_date
 from pandas.tseries.timedeltas import to_timedelta
@@ -126,7 +126,7 @@ def _new_DatetimeIndex(cls, d):
         result = result.tz_localize('UTC').tz_convert(tz)
     return result
 
-class DatetimeIndex(DatelikeOps, DatetimeIndexOpsMixin, Int64Index):
+class DatetimeIndex(DatelikeOps, TimelikeOps, 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/offsets.py

@@ -496,6 +496,10 @@ def freqstr(self):
 
         return fstr
 
+    @property
+    def nanos(self):
+        raise ValueError("{0} is a non-fixed frequency".format(self))
+
 class SingleConstructorOffset(DateOffset):
 
     @classmethod

pandas/tseries/tdi.py

@@ -12,7 +12,7 @@
 from pandas.tseries.frequencies import to_offset
 import pandas.core.common as com
 from pandas.tseries import timedeltas
-from pandas.tseries.base import DatetimeIndexOpsMixin
+from pandas.tseries.base import TimelikeOps, DatetimeIndexOpsMixin
 from pandas.tseries.timedeltas import to_timedelta, _coerce_scalar_to_timedelta_type
 import pandas.tseries.offsets as offsets
 from pandas.tseries.offsets import Tick, DateOffset
@@ -24,16 +24,6 @@
 
 Timedelta = tslib.Timedelta
 
-_resolution_map = {
-    'ns' : offsets.Nano,
-    'us' : offsets.Micro,
-    'ms' : offsets.Milli,
-    's'  : offsets.Second,
-    'm'  : offsets.Minute,
-    'h'  : offsets.Hour,
-    'D'  : offsets.Day,
-    }
-
 def _td_index_cmp(opname, nat_result=False):
     """
     Wrap comparison operations to convert timedelta-like to timedelta64
@@ -73,7 +63,7 @@ def wrapper(self, other):
     return wrapper
 
 
-class TimedeltaIndex(DatetimeIndexOpsMixin, Int64Index):
+class TimedeltaIndex(DatetimeIndexOpsMixin, TimelikeOps, Int64Index):
     """
     Immutable ndarray of timedelta64 data, represented internally as int64, and
     which can be boxed to timedelta objects
@@ -706,7 +696,7 @@ def _maybe_cast_slice_bound(self, label, side, kind):
             if side == 'left':
                 return lbound
             else:
-                return (lbound + _resolution_map[parsed.resolution]() -
+                return (lbound + to_offset(parsed.resolution) -
                         Timedelta(1, 'ns'))
         elif is_integer(label) or is_float(label):
             self._invalid_indexer('slice',label)
@@ -734,9 +724,8 @@ def _partial_td_slice(self, key, freq, use_lhs=True, use_rhs=True):
 
         # figure out the resolution of the passed td
         # and round to it
-        reso = parsed.resolution
         t1 = parsed.round(reso)
-        t2 = t1 + _resolution_map[reso]() - Timedelta(1,'ns')
+        t2 = t1 + to_offset(parsed.resolution) - Timedelta(1,'ns')
 
         stamps = self.asi8
 

pandas/tseries/tests/test_timedeltas.py

@@ -74,10 +74,11 @@ def test_construction(self):
         self.assertEqual(Timedelta('-1:00:00'), -timedelta(hours=1))
         self.assertEqual(Timedelta('-01:00:00'), -timedelta(hours=1))
 
-        # more strings
+        # more strings & abbrevs
         # GH 8190
         self.assertEqual(Timedelta('1 h'), timedelta(hours=1))
         self.assertEqual(Timedelta('1 hour'), timedelta(hours=1))
+        self.assertEqual(Timedelta('1 hr'), timedelta(hours=1))
         self.assertEqual(Timedelta('1 hours'), timedelta(hours=1))
         self.assertEqual(Timedelta('-1 hours'), -timedelta(hours=1))
         self.assertEqual(Timedelta('1 m'), timedelta(minutes=1))
@@ -164,6 +165,64 @@ def test_construction(self):
         self.assertEqual(Timedelta(pd.offsets.Hour(2)),Timedelta('0 days, 02:00:00'))
         self.assertEqual(Timedelta(pd.offsets.Second(2)),Timedelta('0 days, 00:00:02'))
 
+    def test_round(self):
+
+        t1 = Timedelta('1 days 02:34:56.789123456')
+        t2 = Timedelta('-1 days 02:34:56.789123456')
+
+        for (freq, s1, s2) in [('N', t1, t2),
+                               ('U', Timedelta('1 days 02:34:56.789123000'),Timedelta('-1 days 02:34:56.789123000')),
+                               ('L', Timedelta('1 days 02:34:56.789000000'),Timedelta('-1 days 02:34:56.789000000')),
+                               ('S',  Timedelta('1 days 02:34:56'),Timedelta('-1 days 02:34:56')),
+                               ('2S',  Timedelta('1 days 02:34:56'),Timedelta('-1 days 02:34:56')),
+                               ('5S',  Timedelta('1 days 02:34:55'),Timedelta('-1 days 02:34:55')),
+                               ('T',  Timedelta('1 days 02:34:00'),Timedelta('-1 days 02:34:00')),
+                               ('12T',  Timedelta('1 days 02:24:00'),Timedelta('-1 days 02:24:00')),
+                               ('H',  Timedelta('1 days 02:00:00'),Timedelta('-1 days 02:00:00')),
+                               ('d',  Timedelta('1 days'),Timedelta('-1 days'))]:
+            r1 = t1.round(freq)
+            self.assertEqual(r1, s1)
+            r2 = t2.round(freq)
+            self.assertEqual(r2, s2)
+
+        # invalid
+        for freq in ['Y','M','foobar']:
+            self.assertRaises(ValueError, lambda : t1.round(freq))
+
+        t1 = timedelta_range('1 days',periods=3,freq='1 min 2 s 3 us')
+        t2 = -1*t1
+        t1a = timedelta_range('1 days',periods=3,freq='1 min 2 s')
+        t1b = timedelta_range('1 days',periods=3,freq='1 min')
+        t1c = pd.TimedeltaIndex([1,1,1],unit='D')
+
+        # note that negative times round DOWN! so don't give whole numbers
+        for (freq, s1, s2) in [('N', t1, t2),
+                               ('U', t1, t2),
+                               ('L', t1a, TimedeltaIndex(['-1 days +00:00:00', '-2 days +23:58:57.999000',
+                                                          '-2 days +23:57:55.999000'],
+                                                         dtype='timedelta64[ns]', freq=None)),
+                               ('S', t1a, TimedeltaIndex(['-1 days +00:00:00', '-2 days +23:58:57', '-2 days +23:57:55'],
+                                                         dtype='timedelta64[ns]', freq=None)),
+                               ('2S', t1a, TimedeltaIndex(['-1 days +00:00:00', '-2 days +23:58:56', '-2 days +23:57:54'],
+                                                          dtype='timedelta64[ns]', freq=None)),
+                               ('5S', t1b, TimedeltaIndex(['-1 days +00:00:00', '-2 days +23:58:55', '-2 days +23:57:55'],
+                                                          dtype='timedelta64[ns]', freq=None)),
+                               ('T', t1b,  TimedeltaIndex(['-1 days +00:00:00', '-2 days +23:58:00', '-2 days +23:57:00'],
+                                                          dtype='timedelta64[ns]', freq=None)),
+                               ('12T', t1c, TimedeltaIndex(['-1 days +00:00:00', '-2 days +23:48:00', '-2 days +23:48:00'],
+                                                           dtype='timedelta64[ns]', freq=None)),
+                               ('H',  t1c, TimedeltaIndex(['-1 days +00:00:00', '-2 days +23:00:00', '-2 days +23:00:00'],
+                                                          dtype='timedelta64[ns]', freq=None)),
+                               ('d',  t1c, pd.TimedeltaIndex([-1,-2,-2],unit='D'))]:
+            r1 = t1.round(freq)
+            tm.assert_index_equal(r1, s1)
+            r2 = t2.round(freq)
+            tm.assert_index_equal(r2, s2)
+
+        # invalid
+        for freq in ['Y','M','foobar']:
+            self.assertRaises(ValueError, lambda : t1.round(freq))
+
     def test_repr(self):
 
         self.assertEqual(repr(Timedelta(10,unit='d')),"Timedelta('10 days 00:00:00')")