BUG: resampling with NaT in TimedeltaIndex (pandas-dev#13223)

Author: paulgliu

pandas/tseries/resample.py

@@ -354,7 +354,7 @@ def transform(self, arg, *args, **kwargs):
     def _downsample(self, f):
         raise AbstractMethodError(self)
 
-    def _upsample(self, f, limit=None, fill_value=None):
+    def _upsample(self, f, limit=None):
         raise AbstractMethodError(self)
 
     def _gotitem(self, key, ndim, subset=None):
@@ -510,7 +510,7 @@ def interpolate(self, method='linear', axis=0, limit=None, inplace=False,
                                   limit_direction=limit_direction,
                                   downcast=downcast, **kwargs)
 
-    def asfreq(self, fill_value=None):
+    def asfreq(self):
         """
         return the values at the new freq,
         essentially a reindex
@@ -727,7 +727,7 @@ def _adjust_binner_for_upsample(self, binner):
             binner = binner[:-1]
         return binner
 
-    def _upsample(self, method, limit=None, fill_value=None):
+    def _upsample(self, method, limit=None):
         """
         method : string {'backfill', 'bfill', 'pad',
             'ffill', 'asfreq'} method for upsampling
@@ -761,7 +761,7 @@ def _upsample(self, method, limit=None, fill_value=None):
             result.index = res_index
         else:
             result = obj.reindex(res_index, method=method,
-                                 limit=limit, fill_value=fill_value)
+                                 limit=limit)
 
         return self._wrap_result(result)
 
@@ -881,7 +881,7 @@ def _downsample(self, how, **kwargs):
             'Frequency {} cannot be resampled to {}, as they are not '
             'sub or super periods'.format(ax.freq, self.freq))
 
-    def _upsample(self, method, limit=None, fill_value=None):
+    def _upsample(self, method, limit=None):
         """
         method : string {'backfill', 'bfill', 'pad', 'ffill'}
             method for upsampling
@@ -902,8 +902,8 @@ def _upsample(self, method, limit=None, fill_value=None):
                              " datetime-like")
         # we may need to actually resample as if we are timestamps
         if self.kind == 'timestamp':
-            return super(PeriodIndexResampler, self)._upsample(
-                method, limit=limit, fill_value=fill_value)
+            return super(PeriodIndexResampler, self)._upsample(method,
+                                                               limit=limit)
 
         ax = self.ax
         obj = self.obj
@@ -1376,7 +1376,7 @@ def _adjust_dates_anchored(first, last, offset, closed='right', base=0):
             Timestamp(lresult).tz_localize(last_tzinfo, ambiguous=last_dst))
 
 
-def asfreq(obj, freq, method=None, how=None, normalize=False, fill_value=None):
+def asfreq(obj, freq, method=None, how=None, normalize=False):
     """
     Utility frequency conversion method for Series/DataFrame
     """
@@ -1396,7 +1396,7 @@ def asfreq(obj, freq, method=None, how=None, normalize=False, fill_value=None):
             return obj.copy()
         dti = date_range(obj.index[0], obj.index[-1], freq=freq)
         dti.name = obj.index.name
-        rs = obj.reindex(dti, method=method, fill_value=fill_value)
+        rs = obj.reindex(dti, method=method)
         if normalize:
             rs.index = rs.index.normalize()
         return rs

pandas/tseries/tests/test_resample.py

@@ -110,7 +110,7 @@ def test_api_changes_v018(self):
         r = self.series.resample('H')
         self.assertRaises(ValueError, lambda: r.iloc[0])
         self.assertRaises(ValueError, lambda: r.iat[0])
-        self.assertRaises(ValueError, lambda: r.loc[0])
+        self.assertRaises(ValueError, lambda: r.ix[0])
         self.assertRaises(ValueError, lambda: r.loc[
             Timestamp('2013-01-01 00:00:00', offset='H')])
         self.assertRaises(ValueError, lambda: r.at[