API: Datetime-like indexes summary should output the same format

doc/source/whatsnew/v0.16.0.txt

@@ -29,6 +29,10 @@ Backwards incompatible API changes
 
 - ``Index.duplicated`` now returns `np.array(dtype=bool)` rather than `Index(dtype=object)` containing `bool` values. (:issue:`8875`)
 
+- ``DatetimeIndex``, ``PeriodIndex`` and ``TimedeltaIndex.summary`` now output the same format. (:issue:`9116`)
+- ``TimedeltaIndex.freqstr`` now output the same string format as ``DatetimeIndex``. (:issue:`9116`)
+
+
 Deprecations
 ~~~~~~~~~~~~
 

pandas/tseries/base.py

@@ -69,6 +69,13 @@ def __contains__(self, key):
         except (KeyError, TypeError):
             return False
 
+    @property
+    def freqstr(self):
+        """ return the frequency object as a string if its set, otherwise None """
+        if self.freq is None:
+            return None
+        return self.freq.freqstr
+
     @cache_readonly
     def inferred_freq(self):
         try:
@@ -459,3 +466,23 @@ def repeat(self, repeats, axis=None):
         """
         return self._simple_new(self.values.repeat(repeats),
                                 name=self.name)
+
+    def summary(self, name=None):
+        """
+        return a summarized representation
+        """
+        formatter = self._formatter_func
+        if len(self) > 0:
+            index_summary = ', %s to %s' % (formatter(self[0]),
+                                            formatter(self[-1]))
+        else:
+            index_summary = ''
+
+        if name is None:
+            name = type(self).__name__
+        result = '%s: %s entries%s' % (com.pprint_thing(name),
+                                       len(self), index_summary)
+        if self.freq:
+            result += '\nFreq: %s' % self.freqstr
+
+        return result

pandas/tseries/index.py

@@ -682,22 +682,6 @@ def _format_native_types(self, na_rep=u('NaT'),
     def to_datetime(self, dayfirst=False):
         return self.copy()
 
-    def summary(self, name=None):
-        if len(self) > 0:
-            index_summary = ', %s to %s' % (com.pprint_thing(self[0]),
-                                            com.pprint_thing(self[-1]))
-        else:
-            index_summary = ''
-
-        if name is None:
-            name = type(self).__name__
-        result = '%s: %s entries%s' % (com.pprint_thing(name),
-                                       len(self), index_summary)
-        if self.freq:
-            result += '\nFreq: %s' % self.freqstr
-
-        return result
-
     def _format_footer(self):
         tagline = 'Length: %d, Freq: %s, Timezone: %s'
         return tagline % (len(self), self.freqstr, self.tz)
@@ -1392,13 +1376,6 @@ def _set_freq(self, value):
         self.offset = value
     freq = property(fget=_get_freq, fset=_set_freq, doc="get/set the frequncy of the Index")
 
-    @property
-    def freqstr(self):
-        """ return the frequency object as a string if its set, otherwise None """
-        if self.freq is None:
-            return None
-        return self.offset.freqstr
-
     year = _field_accessor('year', 'Y', "The year of the datetime")
     month = _field_accessor('month', 'M', "The month as January=1, December=12")
     day = _field_accessor('day', 'D', "The days of the datetime")

pandas/tseries/tdi.py

@@ -410,23 +410,6 @@ def f(x):
             result = result.astype('int64')
         return result
 
-    def summary(self, name=None):
-        formatter = self._formatter_func
-        if len(self) > 0:
-            index_summary = ', %s to %s' % (formatter(self[0]),
-                                            formatter(self[-1]))
-        else:
-            index_summary = ''
-
-        if name is None:
-            name = type(self).__name__
-        result = '%s: %s entries%s' % (com.pprint_thing(name),
-                                       len(self), index_summary)
-        if self.freq:
-            result += '\nFreq: %s' % self.freqstr
-
-        return result
-
     def to_pytimedelta(self):
         """
         Return TimedeltaIndex as object ndarray of datetime.timedelta objects
@@ -796,13 +779,6 @@ def __getitem__(self, key):
 
             return self._simple_new(result, self.name)
 
-    @property
-    def freqstr(self):
-        """ return the frequency object as a string if its set, otherwise None """
-        if self.freq is None:
-            return None
-        return self.freq
-
     def searchsorted(self, key, side='left'):
         if isinstance(key, (np.ndarray, Index)):
             key = np.array(key, dtype=_TD_DTYPE, copy=False)

pandas/tseries/tests/test_base.py

@@ -143,6 +143,34 @@ def test_representation(self):
                 result = getattr(idx, func)()
                 self.assertEqual(result, expected)
 
+    def test_summary(self):
+        # GH9116
+        idx1 = DatetimeIndex([], freq='D')
+        idx2 = DatetimeIndex(['2011-01-01'], freq='D')
+        idx3 = DatetimeIndex(['2011-01-01', '2011-01-02'], freq='D')
+        idx4 = DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03'], freq='D')
+        idx5 = DatetimeIndex(['2011-01-01 09:00', '2011-01-01 10:00', '2011-01-01 11:00'],
+                             freq='H', tz='Asia/Tokyo')
+        idx6 = DatetimeIndex(['2011-01-01 09:00', '2011-01-01 10:00', pd.NaT],
+                             tz='US/Eastern')
+
+        exp1 = """DatetimeIndex: 0 entries
+Freq: D"""
+        exp2 = """DatetimeIndex: 1 entries, 2011-01-01 to 2011-01-01
+Freq: D"""
+        exp3 = """DatetimeIndex: 2 entries, 2011-01-01 to 2011-01-02
+Freq: D"""
+        exp4 = """DatetimeIndex: 3 entries, 2011-01-01 to 2011-01-03
+Freq: D"""
+        exp5 = """DatetimeIndex: 3 entries, 2011-01-01 09:00:00+09:00 to 2011-01-01 11:00:00+09:00
+Freq: H"""
+        exp6 = """DatetimeIndex: 3 entries, 2011-01-01 09:00:00-05:00 to NaT"""
+
+        for idx, expected in zip([idx1, idx2, idx3, idx4, idx5, idx6],
+                                 [exp1, exp2, exp3, exp4, exp5, exp6]):
+            result = idx.summary()
+            self.assertEqual(result, expected)
+
     def test_resolution(self):
         for freq, expected in zip(['A', 'Q', 'M', 'D', 'H', 'T', 'S', 'L', 'U'],
                                   ['day', 'day', 'day', 'day',
@@ -336,16 +364,16 @@ def test_representation(self):
 
 
         exp1 = """<class 'pandas.tseries.tdi.TimedeltaIndex'>
-Length: 0, Freq: <Day>"""
+Length: 0, Freq: D"""
         exp2 = """<class 'pandas.tseries.tdi.TimedeltaIndex'>
 ['1 days']
-Length: 1, Freq: <Day>"""
+Length: 1, Freq: D"""
         exp3 = """<class 'pandas.tseries.tdi.TimedeltaIndex'>
 ['1 days', '2 days']
-Length: 2, Freq: <Day>"""
+Length: 2, Freq: D"""
         exp4 = """<class 'pandas.tseries.tdi.TimedeltaIndex'>
 ['1 days', ..., '3 days']
-Length: 3, Freq: <Day>"""
+Length: 3, Freq: D"""
         exp5 = """<class 'pandas.tseries.tdi.TimedeltaIndex'>
 ['1 days 00:00:01', ..., '3 days 00:00:00']
 Length: 3, Freq: None"""
@@ -356,6 +384,29 @@ def test_representation(self):
                 result = getattr(idx, func)()
                 self.assertEqual(result, expected)
 
+    def test_summary(self):
+        # GH9116
+        idx1 = TimedeltaIndex([], freq='D')
+        idx2 = TimedeltaIndex(['1 days'], freq='D')
+        idx3 = TimedeltaIndex(['1 days', '2 days'], freq='D')
+        idx4 = TimedeltaIndex(['1 days', '2 days', '3 days'], freq='D')
+        idx5 = TimedeltaIndex(['1 days 00:00:01', '2 days', '3 days'])
+
+        exp1 = """TimedeltaIndex: 0 entries
+Freq: D"""
+        exp2 = """TimedeltaIndex: 1 entries, '1 days' to '1 days'
+Freq: D"""
+        exp3 = """TimedeltaIndex: 2 entries, '1 days' to '2 days'
+Freq: D"""
+        exp4 = """TimedeltaIndex: 3 entries, '1 days' to '3 days'
+Freq: D"""
+        exp5 = """TimedeltaIndex: 3 entries, '1 days 00:00:01' to '3 days 00:00:00'"""
+
+        for idx, expected in zip([idx1, idx2, idx3, idx4, idx5],
+                                 [exp1, exp2, exp3, exp4, exp5]):
+            result = idx.summary()
+            self.assertEqual(result, expected)
+
     def test_add_iadd(self):
 
         # only test adding/sub offsets as + is now numeric
@@ -755,6 +806,43 @@ def test_representation(self):
                 result = getattr(idx, func)()
                 self.assertEqual(result, expected)
 
+    def test_summary(self):
+        # GH9116
+        idx1 = PeriodIndex([], freq='D')
+        idx2 = PeriodIndex(['2011-01-01'], freq='D')
+        idx3 = PeriodIndex(['2011-01-01', '2011-01-02'], freq='D')
+        idx4 = PeriodIndex(['2011-01-01', '2011-01-02', '2011-01-03'], freq='D')
+        idx5 = PeriodIndex(['2011', '2012', '2013'], freq='A')
+        idx6 = PeriodIndex(['2011-01-01 09:00', '2012-02-01 10:00', 'NaT'], freq='H')
+
+        idx7 = pd.period_range('2013Q1', periods=1, freq="Q")
+        idx8 = pd.period_range('2013Q1', periods=2, freq="Q")
+        idx9 = pd.period_range('2013Q1', periods=3, freq="Q")
+
+        exp1 = """PeriodIndex: 0 entries
+Freq: D"""
+        exp2 = """PeriodIndex: 1 entries, 2011-01-01 to 2011-01-01
+Freq: D"""
+        exp3 = """PeriodIndex: 2 entries, 2011-01-01 to 2011-01-02
+Freq: D"""
+        exp4 = """PeriodIndex: 3 entries, 2011-01-01 to 2011-01-03
+Freq: D"""
+        exp5 = """PeriodIndex: 3 entries, 2011 to 2013
+Freq: A-DEC"""
+        exp6 = """PeriodIndex: 3 entries, 2011-01-01 09:00 to NaT
+Freq: H"""
+        exp7 = """PeriodIndex: 1 entries, 2013Q1 to 2013Q1
+Freq: Q-DEC"""
+        exp8 = """PeriodIndex: 2 entries, 2013Q1 to 2013Q2
+Freq: Q-DEC"""
+        exp9 = """PeriodIndex: 3 entries, 2013Q1 to 2013Q3
+Freq: Q-DEC"""
+
+        for idx, expected in zip([idx1, idx2, idx3, idx4, idx5, idx6, idx7, idx8, idx9],
+                                 [exp1, exp2, exp3, exp4, exp5, exp6, exp7, exp8, exp9]):
+            result = idx.summary()
+            self.assertEqual(result, expected)
+
     def test_resolution(self):
         for freq, expected in zip(['A', 'Q', 'M', 'D', 'H', 'T', 'S', 'L', 'U'],
                                   ['day', 'day', 'day', 'day',

pandas/tseries/tests/test_timedeltas.py

@@ -540,7 +540,7 @@ def conv(v):
         expected = np.array([0, 500000000, 800000000, 1200000000], dtype='timedelta64[ns]')
         result = to_timedelta([0., 0.5, 0.8, 1.2], unit='s', box=False)
         tm.assert_numpy_array_equal(expected, result)
-       
+
         def testit(unit, transform):
 
             # array