Resampler.__iter__ is returned iterable obj

Author: discort

doc/source/timeseries.rst

@@ -703,6 +703,23 @@ regularity will result in a ``DatetimeIndex``, although frequency is lost:
 
    ts2[[0, 2, 6]].index
 
+.. _timeseries.iterating:
+
+Iterating through groups
+------------------------
+
+With the Resampler object in hand, iterating through the grouped data is very
+natural and functions similarly to :py:func:`itertools.groupby`:
+
+.. ipython::
+
+   In [1]: resampled = df.resample('H')
+
+   In [2]: for name, group in resampled:
+      ...:        print(name)
+      ...:        print(group)
+      ...:
+
 .. _timeseries.components:
 
 Time/Date Components

doc/source/whatsnew/v0.24.0.txt

@@ -182,6 +182,7 @@ Other Enhancements
 - :func:`to_timedelta` now supports iso-formated timedelta strings (:issue:`21877`)
 - :class:`Series` and :class:`DataFrame` now support :class:`Iterable` in constructor (:issue:`2193`)
 - :class:`DatetimeIndex` gained :attr:`DatetimeIndex.timetz` attribute. Returns local time with timezone information. (:issue:`21358`)
+- :class:`Resampler` now is iterable like :class:`GroupBy` (:issue:`15314`).
 
 .. _whatsnew_0240.api_breaking:
 

pandas/core/resample.py

@@ -97,6 +97,23 @@ def __getattr__(self, attr):
 
         return object.__getattribute__(self, attr)
 
+    def __iter__(self):
+        """
+        Resampler iterator
+
+        Returns
+        -------
+        Generator yielding sequence of (name, subsetted object)
+        for each group
+
+        See Also
+        --------
+        GroupBy.__iter__
+
+        """
+        self._set_binner()
+        return super(Resampler, self).__iter__()
+
     @property
     def obj(self):
         return self.groupby.obj

pandas/tests/test_resample.py

@@ -771,6 +771,17 @@ def test_apply_to_empty_series(self):
 
             assert_series_equal(result, expected, check_dtype=False)
 
+    def test_resampler_is_iterable(self):
+        # GH 15314
+        series = self.create_series()
+        freq = 'H'
+        tg = TimeGrouper(freq, convention='start')
+        grouped = series.groupby(tg)
+        resampled = series.resample(freq)
+        for (rk, rv), (gk, gv) in zip(resampled, grouped):
+            assert rk == gk
+            assert_series_equal(rv, gv)
+
 
 class TestDatetimeIndex(Base):
     _index_factory = lambda x: date_range