CLN: Simplify Period Construction / Resolution

pandas/io/tests/generate_legacy_pickles.py

@@ -58,7 +58,7 @@ def create_data():
     from pandas import (Series,TimeSeries,DataFrame,Panel,
                         SparseSeries,SparseTimeSeries,SparseDataFrame,SparsePanel,
                         Index,MultiIndex,PeriodIndex,
-                        date_range,bdate_range,Timestamp)
+                        date_range,period_range,bdate_range,Timestamp)
     nan = np.nan
 
     data = {
@@ -70,7 +70,9 @@ def create_data():
         }
 
     index = dict(int = Index(np.arange(10)),
-                  date = date_range('20130101',periods=10))
+                 date = date_range('20130101',periods=10),
+                 period = period_range('2013-01-01', freq='M', periods=10))
+
     mi = dict(reg2 = MultiIndex.from_tuples(tuple(zip(*[['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
                                                       ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']])),
                                                  names=['first', 'second']))

pandas/tseries/frequencies.py

@@ -30,20 +30,40 @@ class FreqGroup(object):
 
 class Resolution(object):
 
-    RESO_US = 0
-    RESO_SEC = 1
-    RESO_MIN = 2
-    RESO_HR = 3
-    RESO_DAY = 4
+    RESO_US = tslib.US_RESO
+    RESO_MS = tslib.MS_RESO
+    RESO_SEC = tslib.S_RESO
+    RESO_MIN = tslib.T_RESO
+    RESO_HR = tslib.H_RESO
+    RESO_DAY = tslib.D_RESO
+
+    _reso_str_map = {
+    RESO_US: 'microsecond',
+    RESO_MS: 'millisecond',
+    RESO_SEC: 'second',
+    RESO_MIN: 'minute',
+    RESO_HR: 'hour',
+    RESO_DAY: 'day'}
+
+    _reso_period_map = {
+    'year': 'A',
+    'quarter': 'Q',
+    'month': 'M',
+    'day': 'D',
+    'hour': 'H',
+    'minute': 'T',
+    'second': 'S',
+    'millisecond': 'L',
+    'microsecond': 'U',
+    'nanosecond': 'N'}
 
     @classmethod
     def get_str(cls, reso):
-        return {cls.RESO_US: 'microsecond',
-                cls.RESO_SEC: 'second',
-                cls.RESO_MIN: 'minute',
-                cls.RESO_HR: 'hour',
-                cls.RESO_DAY: 'day'}.get(reso, 'day')
+        return cls._reso_str_map.get(reso, 'day')
 
+    @classmethod
+    def get_freq(cls, resostr):
+        return cls._reso_period_map[resostr]
 
 def get_reso_string(reso):
     return Resolution.get_str(reso)
@@ -571,22 +591,9 @@ def _period_alias_dictionary():
 
     return alias_dict
 
-_reso_period_map = {
-    "year": "A",
-    "quarter": "Q",
-    "month": "M",
-    "day": "D",
-    "hour": "H",
-    "minute": "T",
-    "second": "S",
-    "millisecond": "L",
-    "microsecond": "U",
-    "nanosecond": "N",
-}
-
 
 def _infer_period_group(freqstr):
-    return _period_group(_reso_period_map[freqstr])
+    return _period_group(Resolution._reso_period_map[freqstr])
 
 
 def _period_group(freqstr):

pandas/tseries/period.py

@@ -111,8 +111,14 @@ def __init__(self, value=None, freq=None, ordinal=None,
         elif isinstance(value, compat.string_types) or com.is_integer(value):
             if com.is_integer(value):
                 value = str(value)
+            value = value.upper()
 
-            dt, freq = _get_date_and_freq(value, freq)
+            dt, _, reso = parse_time_string(value, freq)
+            if freq is None:
+                try:
+                    freq = _freq_mod.Resolution.get_freq(reso)
+                except KeyError:
+                    raise ValueError("Invalid frequency or could not infer: %s" % reso)
 
         elif isinstance(value, datetime):
             dt = value
@@ -451,36 +457,6 @@ def strftime(self, fmt):
         return tslib.period_format(self.ordinal, base, fmt)
 
 
-def _get_date_and_freq(value, freq):
-    value = value.upper()
-    dt, _, reso = parse_time_string(value, freq)
-
-    if freq is None:
-        if reso == 'year':
-            freq = 'A'
-        elif reso == 'quarter':
-            freq = 'Q'
-        elif reso == 'month':
-            freq = 'M'
-        elif reso == 'day':
-            freq = 'D'
-        elif reso == 'hour':
-            freq = 'H'
-        elif reso == 'minute':
-            freq = 'T'
-        elif reso == 'second':
-            freq = 'S'
-        elif reso == 'microsecond':
-            if dt.microsecond % 1000 == 0:
-                freq = 'L'
-            else:
-                freq = 'U'
-        else:
-            raise ValueError("Invalid frequency or could not infer: %s" % reso)
-
-    return dt, freq
-
-
 def _get_ordinals(data, freq):
     f = lambda x: Period(x, freq=freq).ordinal
     if isinstance(data[0], Period):

pandas/tseries/tests/test_period.py

@@ -227,6 +227,14 @@ def test_period_constructor(self):
         i2 = Period(datetime(2007, 1, 1), freq='M')
         self.assertEqual(i1, i2)
 
+        i1 = Period('2007-01-01 09:00:00.001')
+        expected = Period(datetime(2007, 1, 1, 9, 0, 0, 1000), freq='L')
+        self.assertEqual(i1, expected)
+
+        i1 = Period('2007-01-01 09:00:00.00101')
+        expected = Period(datetime(2007, 1, 1, 9, 0, 0, 1010), freq='U')
+        self.assertEqual(i1, expected)
+
         self.assertRaises(ValueError, Period, ordinal=200701)
 
         self.assertRaises(ValueError, Period, '2007-1-1', freq='X')

pandas/tseries/tests/test_tslib.py

@@ -476,6 +476,17 @@ def test_addition_subtraction_preserve_frequency(self):
             self.assertEqual((timestamp_instance + timedelta64_instance).freq, original_freq)
             self.assertEqual((timestamp_instance - timedelta64_instance).freq, original_freq)
 
+    def test_resolution(self):
+
+        for freq, expected in zip(['A', 'Q', 'M', 'D', 'H', 'T', 'S', 'L', 'U'],
+                                  [tslib.D_RESO, tslib.D_RESO, tslib.D_RESO, tslib.D_RESO,
+                                   tslib.H_RESO, tslib.T_RESO,tslib.S_RESO, tslib.MS_RESO, tslib.US_RESO]):
+            for tz in [None, 'Asia/Tokyo', 'US/Eastern']:
+                idx = date_range(start='2013-04-01', periods=30, freq=freq, tz=tz)
+                result = tslib.resolution(idx.asi8, idx.tz)
+                self.assertEqual(result, expected)
+
+
 if __name__ == '__main__':
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],
                    exit=False)

pandas/tseries/tools.py

@@ -508,8 +508,11 @@ def dateutil_parse(timestr, default,
     if reso is None:
         raise ValueError("Cannot parse date.")
 
-    if reso == 'microsecond' and repl['microsecond'] == 0:
-        reso = 'second'
+    if reso == 'microsecond':
+        if repl['microsecond'] == 0:
+            reso = 'second'
+        elif repl['microsecond'] % 1000 == 0:
+            reso = 'millisecond'
 
     ret = default.replace(**repl)
     if res.weekday is not None and not res.day:

pandas/tslib.pyx

@@ -3372,13 +3372,16 @@ cpdef resolution(ndarray[int64_t] stamps, tz=None):
         return reso
 
 US_RESO = 0
-S_RESO = 1
-T_RESO = 2
-H_RESO = 3
-D_RESO = 4
+MS_RESO = 1
+S_RESO = 2
+T_RESO = 3
+H_RESO = 4
+D_RESO = 5
 
 cdef inline int _reso_stamp(pandas_datetimestruct *dts):
     if dts.us != 0:
+        if dts.us % 1000 == 0:
+            return MS_RESO
         return US_RESO
     elif dts.sec != 0:
         return S_RESO