CLN: Enforce deprecation of PeriodIndex in resample

pandas/api/typing/__init__.py

@@ -14,7 +14,6 @@
 from pandas.core.indexes.frozen import FrozenList
 from pandas.core.resample import (
     DatetimeIndexResamplerGroupby,
-    PeriodIndexResamplerGroupby,
     Resampler,
     TimedeltaIndexResamplerGroupby,
     TimeGrouper,
@@ -48,7 +47,6 @@
     "NAType",
     "NaTType",
     "NoDefault",
-    "PeriodIndexResamplerGroupby",
     "Resampler",
     "Rolling",
     "RollingGroupby",

pandas/core/generic.py

@@ -8835,12 +8835,6 @@ def resample(
             Which bin edge label to label bucket with. The default is 'left'
             for all frequency offsets except for 'ME', 'YE', 'QE', 'BME',
             'BA', 'BQE', and 'W' which all have a default of 'right'.
-        convention : {{'start', 'end', 's', 'e'}}, default 'start'
-            For `PeriodIndex` only, controls whether to use the start or
-            end of `rule`.
-
-            .. deprecated:: 2.2.0
-                Convert PeriodIndex to DatetimeIndex before resampling instead.
         on : str, optional
             For a DataFrame, column to use instead of index for resampling.
             Column must be datetime-like.

pandas/core/resample.py

@@ -19,7 +19,6 @@
 from pandas._libs import lib
 from pandas._libs.tslibs import (
     BaseOffset,
-    IncompatibleFrequency,
     NaT,
     Period,
     Timedelta,
@@ -79,10 +78,6 @@
 )
 from pandas.core.reshape.concat import concat
 
-from pandas.tseries.frequencies import (
-    is_subperiod,
-    is_superperiod,
-)
 from pandas.tseries.offsets import (
     Day,
     Tick,
@@ -1938,128 +1933,6 @@ def _resampler_cls(self):
         return DatetimeIndexResampler
 
 
-class PeriodIndexResampler(DatetimeIndexResampler):
-    # error: Incompatible types in assignment (expression has type "PeriodIndex", base
-    # class "DatetimeIndexResampler" defined the type as "DatetimeIndex")
-    ax: PeriodIndex  # type: ignore[assignment]
-
-    @property
-    def _resampler_for_grouping(self):
-        # TODO: Enforce in 3.0 (#55968)
-        warnings.warn(
-            "Resampling a groupby with a PeriodIndex is deprecated. "
-            "Cast to DatetimeIndex before resampling instead.",
-            FutureWarning,  # pdlint: ignore[warning_class]
-            stacklevel=find_stack_level(),
-        )
-        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:
-        obj = super()._convert_obj(obj)
-
-        if self._from_selection:
-            # see GH 14008, GH 12871
-            msg = (
-                "Resampling from level= or on= selection "
-                "with a PeriodIndex is not currently supported, "
-                "use .set_index(...) to explicitly set index"
-            )
-            raise NotImplementedError(msg)
-
-        # convert to timestamp
-        if isinstance(obj, DatetimeIndex):
-            obj = obj.to_timestamp(how=self.convention)
-
-        return obj
-
-    def _downsample(self, how, **kwargs):
-        """
-        Downsample the cython defined function.
-
-        Parameters
-        ----------
-        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):
-            # Downsampling
-            return self._groupby_and_aggregate(how, **kwargs)
-        elif is_superperiod(ax.freq, self.freq):
-            if how == "ohlc":
-                # GH #13083
-                # upsampling to subperiods is handled as an asfreq, which works
-                # for pure aggregating/reducing methods
-                # OHLC reduces along the time dimension, but creates multiple
-                # values for each period -> handle by _groupby_and_aggregate()
-                return self._groupby_and_aggregate(how)
-            return self.asfreq()
-        elif ax.freq == self.freq:
-            return self.asfreq()
-
-        raise IncompatibleFrequency(
-            f"Frequency {ax.freq} cannot be resampled to {self.freq}, "
-            "as they are not sub or super periods"
-        )
-
-    def _upsample(self, method, limit: int | None = None, fill_value=None):
-        """
-        Parameters
-        ----------
-        method : {'backfill', 'bfill', 'pad', 'ffill'}
-            Method for upsampling.
-        limit : int, default None
-            Maximum size gap to fill when reindexing.
-        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
-
-        # Start vs. end of period
-        memb = ax.asfreq(self.freq, how=self.convention)
-
-        # Get the fill indexer
-        if method == "asfreq":
-            method = None
-        indexer = memb.get_indexer(new_index, method=method, limit=limit)
-        new_obj = _take_new_index(
-            obj,
-            indexer,
-            new_index,
-        )
-        return self._wrap_result(new_obj)
-
-
-# error: Definition of "ax" in base class "_GroupByMixin" is incompatible with
-# definition in base class "PeriodIndexResampler"
-class PeriodIndexResamplerGroupby(  # type: ignore[misc]
-    _GroupByMixin, PeriodIndexResampler
-):
-    """
-    Provides a resample of a groupby implementation.
-    """
-
-    @property
-    def _resampler_cls(self):
-        return PeriodIndexResampler
-
-
 class TimedeltaIndexResampler(DatetimeIndexResampler):
     # error: Incompatible types in assignment (expression has type "TimedeltaIndex",
     # base class "DatetimeIndexResampler" defined the type as "DatetimeIndex")
@@ -2292,20 +2165,9 @@ def _get_resampler(self, obj: NDFrame) -> Resampler:
                 gpr_index=ax,
             )
         elif isinstance(ax, PeriodIndex):
-            if isinstance(ax, PeriodIndex):
-                # TODO: Enforce in 3.0 (#53481)
-                # GH#53481
-                warnings.warn(
-                    "Resampling with a PeriodIndex is deprecated. "
-                    "Cast index to DatetimeIndex before resampling instead.",
-                    FutureWarning,  # pdlint: ignore[warning_class]
-                    stacklevel=find_stack_level(),
-                )
-            return PeriodIndexResampler(
-                obj,
-                timegrouper=self,
-                group_keys=self.group_keys,
-                gpr_index=ax,
+            raise TypeError(
+                "Resampling with a PeriodIndex is not supported. "
+                "Cast index to DatetimeIndex before resampling instead.",
             )
         elif isinstance(ax, TimedeltaIndex):
             return TimedeltaIndexResampler(

pandas/tests/api/test_api.py

@@ -267,7 +267,6 @@ class TestApi(Base):
         "NaTType",
         "NAType",
         "NoDefault",
-        "PeriodIndexResamplerGroupby",
         "Resampler",
         "Rolling",
         "RollingGroupby",