update Appender to doc in category.py

Author: HH-MWB

pandas/core/indexes/category.py

@@ -9,7 +9,7 @@
 from pandas._libs.hashtable import duplicated_int64
 from pandas._libs.lib import no_default
 from pandas._typing import Label
-from pandas.util._decorators import Appender, cache_readonly
+from pandas.util._decorators import Appender, cache_readonly, doc
 
 from pandas.core.dtypes.common import (
     ensure_platform_int,
@@ -241,7 +241,7 @@ def _simple_new(cls, values: Categorical, name: Label = None):
 
     # --------------------------------------------------------------------
 
-    @Appender(Index._shallow_copy.__doc__)
+    @doc(Index._shallow_copy)
     def _shallow_copy(self, values=None, name: Label = no_default):
         if values is not None:
             values = Categorical(values, dtype=self.dtype)
@@ -351,7 +351,7 @@ def _has_complex_internals(self) -> bool:
         # used to avoid libreduction code paths, which raise or require conversion
         return True
 
-    @Appender(Index.__contains__.__doc__)
+    @doc(Index.__contains__)
     def __contains__(self, key: Any) -> bool:
         # if key is a NaN, check if any NaN is in self.
         if is_scalar(key) and isna(key):
@@ -360,7 +360,7 @@ def __contains__(self, key: Any) -> bool:
         hash(key)
         return contains(self, key, container=self._engine)
 
-    @Appender(Index.astype.__doc__)
+    @doc(Index.astype)
     def astype(self, dtype, copy=True):
         if is_interval_dtype(dtype):
             from pandas import IntervalIndex
@@ -379,7 +379,7 @@ def _isnan(self):
         """ return if each value is nan"""
         return self._data.codes == -1
 
-    @Appender(Index.fillna.__doc__)
+    @doc(Index.fillna)
     def fillna(self, value, downcast=None):
         self._assert_can_do_op(value)
         return CategoricalIndex(self._data.fillna(value), name=self.name)
@@ -392,7 +392,7 @@ def _engine(self):
         codes = self.codes
         return self._engine_type(lambda: codes, len(self))
 
-    @Appender(Index.unique.__doc__)
+    @doc(Index.unique)
     def unique(self, level=None):
         if level is not None:
             self._validate_index_level(level)
@@ -401,7 +401,7 @@ def unique(self, level=None):
         #  of result, not self.
         return type(self)._simple_new(result, name=self.name)
 
-    @Appender(Index.duplicated.__doc__)
+    @doc(Index.duplicated)
     def duplicated(self, keep="first"):
         codes = self.codes.astype("i8")
         return duplicated_int64(codes, keep)
@@ -415,7 +415,7 @@ def _maybe_cast_indexer(self, key):
         code = self.codes.dtype.type(code)
         return code
 
-    @Appender(Index.where.__doc__)
+    @doc(Index.where)
     def where(self, cond, other=None):
         # TODO: Investigate an alternative implementation with
         # 1. copy the underlying Categorical
@@ -566,7 +566,7 @@ def get_indexer_non_unique(self, target):
         indexer, missing = self._engine.get_indexer_non_unique(codes)
         return ensure_platform_int(indexer), missing
 
-    @Appender(Index._convert_list_indexer.__doc__)
+    @doc(Index._convert_list_indexer)
     def _convert_list_indexer(self, keyarr):
         # Return our indexer or raise if all of the values are not included in
         # the categories
@@ -583,7 +583,7 @@ def _convert_list_indexer(self, keyarr):
 
         return self.get_indexer(keyarr)
 
-    @Appender(Index._convert_arr_indexer.__doc__)
+    @doc(Index._convert_arr_indexer)
     def _convert_arr_indexer(self, keyarr):
         keyarr = com.asarray_tuplesafe(keyarr)
 
@@ -592,7 +592,7 @@ def _convert_arr_indexer(self, keyarr):
 
         return self._shallow_copy(keyarr)
 
-    @Appender(Index._convert_index_indexer.__doc__)
+    @doc(Index._convert_index_indexer)
     def _convert_index_indexer(self, keyarr):
         return self._shallow_copy(keyarr)
 
@@ -605,7 +605,7 @@ def take_nd(self, *args, **kwargs):
         )
         return self.take(*args, **kwargs)
 
-    @Appender(Index._maybe_cast_slice_bound.__doc__)
+    @doc(Index._maybe_cast_slice_bound)
     def _maybe_cast_slice_bound(self, label, side, kind):
         if kind == "loc":
             return label