PERF: Fix performance regression pandas-dev#33365

Fix performance regression in Series.is_monotonic_increasing for categorical
by avoiding Categorical construction for categorical series

Author: rtlee9

pandas/core/indexes/category.py

@@ -19,6 +19,7 @@
     is_scalar,
 )
 from pandas.core.dtypes.dtypes import CategoricalDtype
+from pandas.core.dtypes.generic import ABCSeries
 from pandas.core.dtypes.missing import isna
 
 from pandas.core import accessor
@@ -30,6 +31,7 @@
 from pandas.core.indexes.extension import ExtensionIndex, inherit_names
 import pandas.core.missing as missing
 from pandas.core.ops import get_op_result_name
+from pandas.core.construction import extract_array
 
 _index_doc_kwargs = dict(ibase._index_doc_kwargs)
 _index_doc_kwargs.update(dict(target_klass="CategoricalIndex"))
@@ -198,8 +200,14 @@ def __new__(
                 data = []
 
         assert isinstance(dtype, CategoricalDtype), dtype
-        if not isinstance(data, Categorical) or data.dtype != dtype:
+        if isinstance(data, (cls, ABCSeries)) and is_categorical_dtype(data):
+            data = extract_array(data)
+
+        if not isinstance(data, Categorical):
             data = Categorical(data, dtype=dtype)
+        elif isinstance(dtype, CategoricalDtype) and dtype != data.dtype:
+            # we want to silently ignore dtype='category'
+            data = data._set_dtype(dtype)
 
         data = data.copy() if copy else data