added explicit 'size' method and defined logic there

Author: discort

doc/source/whatsnew/v0.19.0.txt

@@ -1563,4 +1563,3 @@ Bug Fixes
 - ``PeriodIndex`` can now accept ``list`` and ``array`` which contains ``pd.NaT`` (:issue:`13430`)
 - Bug in ``df.groupby`` where ``.median()`` returns arbitrary values if grouped dataframe contains empty bins (:issue:`13629`)
 - Bug in ``Index.copy()`` where ``name`` parameter was ignored (:issue:`14302`)
-- Bug in ``_downsample()``. Inconsistent return type on resample of empty DataFrame (:issue:`14962`)

doc/source/whatsnew/v0.20.0.txt

@@ -446,7 +446,7 @@ Bug Fixes
 - Bug in ``pd.merge_asof()`` where ``left_index``/``right_index`` together caused a failure when ``tolerance`` was specified (:issue:`15135`)
 
 
-
+- Bug in ``resample().size()``. Inconsistent return type on resample of empty DataFrame (:issue:`14962`)
 
 
 - Bug in ``Series`` constructor when both ``copy=True`` and ``dtype`` arguments are provided (:issue:`15125`)
@@ -460,11 +460,4 @@ Bug Fixes
 - Bug in ``pd.read_csv()`` with ``float_precision='round_trip'`` which caused a segfault when a text entry is parsed (:issue:`15140`)
 
 
-
-
-
-
-
-
-
 - Bug in ``DataFrame.boxplot`` where ``fontsize`` was not applied to the tick labels on both axes (:issue:`15108`)

pandas/tseries/resample.py

@@ -16,6 +16,7 @@
 from pandas.tseries.period import PeriodIndex, period_range
 import pandas.core.common as com
 import pandas.core.algorithms as algos
+from pandas.types.generic import ABCDataFrame
 
 import pandas.compat as compat
 from pandas.compat.numpy import function as nv
@@ -552,6 +553,14 @@ def var(self, ddof=1, *args, **kwargs):
         """
         nv.validate_resampler_func('var', args, kwargs)
         return self._downsample('var', ddof=ddof)
+
+    @Appender(GroupBy.size.__doc__)
+    def size(self):
+        # It 'seems' special and needs extra handling. GH14962
+        result = self._downsample('size')
+        if not len(self.ax) and isinstance(self._selected_obj, ABCDataFrame):
+            result = pd.Series([], index=result.index, dtype='int64')
+        return result
 Resampler._deprecated_valids += dir(Resampler)
 
 # downsample methods
@@ -565,8 +574,7 @@ def f(self, _method=method, *args, **kwargs):
     setattr(Resampler, method, f)
 
 # groupby & aggregate methods
-for method in ['count', 'size']:
-
+for method in ['count']:
     def f(self, _method=method):
         return self._downsample(_method)
     f.__doc__ = getattr(GroupBy, method).__doc__
@@ -772,14 +780,6 @@ def _wrap_result(self, result):
         if self.kind == 'period' and not isinstance(result.index, PeriodIndex):
             result.index = result.index.to_period(self.freq)
 
-        # Make consistent type of result. GH14962
-        if not len(self.ax):
-            grouper = BinGrouper([], result.index)
-            grouped = self._selected_obj.groupby(grouper)
-            result = pd.Series([],
-                               index=result.index,
-                               name=grouped.name,
-                               dtype='int64')
         return result
 
 

pandas/tseries/tests/test_resample.py

@@ -748,7 +748,7 @@ def test_resample_empty_series(self):
                     assert_series_equal(result, expected, check_dtype=False,
                                         check_names=False)
                     # this assert will break when fixed
-                    # self.assertTrue(result.name is None)
+                    self.assertTrue(result.name is None)
                 else:
                     assert_series_equal(result, expected, check_dtype=False)
 
@@ -762,15 +762,22 @@ def test_resample_empty_dataframe(self):
             methods = downsample_methods + upsample_methods
             for method in methods:
                 result = getattr(f.resample(freq), method)()
-
-                expected = pd.Series([])
+                if method != 'size':
+                    expected = f.copy()
+                    assert_equal = assert_frame_equal
+                else:
+                    # GH14962
+                    expected = Series([])
+                    assert_equal = assert_series_equal
+                
                 expected.index = f.index._shallow_copy(freq=freq)
                 assert_index_equal(result.index, expected.index)
                 self.assertEqual(result.index.freq, expected.index.freq)
-                assert_series_equal(result, expected, check_dtype=False)
+                assert_equal(result, expected, check_dtype=False)
 
             # test size for GH13212 (currently stays as df)
 
+
     def test_resample_empty_dtypes(self):
 
         # Empty series were sometimes causing a segfault (for the functions
@@ -824,16 +831,6 @@ def test_resample_loffset_arg_type(self):
                 assert_frame_equal(result_agg, expected)
                 assert_frame_equal(result_how, expected)
 
-    def test_resample_empty_dataframe_with_size(self):
-        # GH 14962
-        index = pd.DatetimeIndex([], freq='M')
-        df = pd.DataFrame([], index=index)
-
-        for freq in ['M', 'D', 'H']:
-            result = df.resample(freq).size()
-            expected = pd.Series([], index=index, dtype='int64')
-            assert_series_equal(result, expected)
-
 
 class TestDatetimeIndex(Base, tm.TestCase):
     _multiprocess_can_split_ = True