CLN: remove unreachable in resample

Author: jbrockmendel

pandas/core/resample.py

@@ -1813,8 +1813,6 @@ def _resampler_for_grouping(self) -> type[DatetimeIndexResamplerGroupby]:
 
     def _get_binner_for_time(self):
         # this is how we are actually creating the bins
-        if isinstance(self.ax, PeriodIndex):
-            return self._timegrouper._get_time_period_bins(self.ax)
         return self._timegrouper._get_time_bins(self.ax)
 
     def _downsample(self, how, **kwargs):
@@ -1838,17 +1836,6 @@ def _downsample(self, how, **kwargs):
             assert obj.index.freq == self.freq, (obj.index.freq, self.freq)
             return obj
 
-        # do we have a regular frequency
-
-        # error: Item "None" of "Optional[Any]" has no attribute "binlabels"
-        if (
-            (ax.freq is not None or ax.inferred_freq is not None)
-            and len(self._grouper.binlabels) > len(ax)
-            and how is None
-        ):
-            # let's do an asfreq
-            return self.asfreq()
-
         # we are downsampling
         # we want to call the actual grouper method here
         result = obj.groupby(self._grouper).aggregate(how, **kwargs)
@@ -1955,8 +1942,6 @@ def _resampler_for_grouping(self):
         return PeriodIndexResamplerGroupby
 
     def _get_binner_for_time(self):
-        if isinstance(self.ax, DatetimeIndex):
-            return super()._get_binner_for_time()
         return self._timegrouper._get_period_bins(self.ax)
 
     def _convert_obj(self, obj: NDFrameT) -> NDFrameT:
@@ -1971,10 +1956,6 @@ def _convert_obj(self, obj: NDFrameT) -> NDFrameT:
             )
             raise NotImplementedError(msg)
 
-        # convert to timestamp
-        if isinstance(obj, DatetimeIndex):
-            obj = obj.to_timestamp(how=self.convention)
-
         return obj
 
     def _downsample(self, how, **kwargs):
@@ -1986,10 +1967,6 @@ def _downsample(self, how, **kwargs):
         how : string / cython mapped function
         **kwargs : kw args passed to how function
         """
-        # we may need to actually resample as if we are timestamps
-        if isinstance(self.ax, DatetimeIndex):
-            return super()._downsample(how, **kwargs)
-
         ax = self.ax
 
         if is_subperiod(ax.freq, self.freq):
@@ -2023,10 +2000,6 @@ def _upsample(self, method, limit: int | None = None, fill_value=None):
         fill_value : scalar, default None
             Value to use for missing values.
         """
-        # we may need to actually resample as if we are timestamps
-        if isinstance(self.ax, DatetimeIndex):
-            return super()._upsample(method, limit=limit, fill_value=fill_value)
-
         ax = self.ax
         obj = self.obj
         new_index = self.binner