diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index dd5ff7781e463..737c130161246 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -26,11 +26,9 @@
     is_dtype_equal,
     is_extension_array_dtype,
     is_integer_dtype,
-    is_iterator,
     is_list_like,
     is_object_dtype,
     is_scalar,
-    is_sequence,
     is_timedelta64_dtype,
     needs_i8_conversion,
 )
@@ -324,7 +322,7 @@ def __init__(
             # of numpy
             values = maybe_infer_to_datetimelike(values, convert_dates=True)
             if not isinstance(values, np.ndarray):
-                values = _convert_to_list_like(values)
+                values = com.convert_to_list_like(values)
 
                 # By convention, empty lists result in object dtype:
                 sanitize_dtype = np.dtype("O") if len(values) == 0 else None
@@ -2647,17 +2645,6 @@ def recode_for_categories(codes: np.ndarray, old_categories, new_categories):
     return new_codes
 
 
-def _convert_to_list_like(list_like):
-    if hasattr(list_like, "dtype"):
-        return list_like
-    if isinstance(list_like, list):
-        return list_like
-    if is_sequence(list_like) or isinstance(list_like, tuple) or is_iterator(list_like):
-        return list(list_like)
-
-    return [list_like]
-
-
 def factorize_from_iterable(values):
     """
     Factorize an input `values` into `categories` and `codes`. Preserves
diff --git a/pandas/core/common.py b/pandas/core/common.py
index bb911c0617242..1ccca5193ab46 100644
--- a/pandas/core/common.py
+++ b/pandas/core/common.py
@@ -4,17 +4,16 @@
 Note: pandas.core.common is *not* part of the public API.
 """
 
-import collections
-from collections import abc
+from collections import abc, defaultdict
 from datetime import datetime, timedelta
 from functools import partial
 import inspect
-from typing import Any, Collection, Iterable, Union
+from typing import Any, Collection, Iterable, List, Union
 
 import numpy as np
 
 from pandas._libs import lib, tslibs
-from pandas._typing import T
+from pandas._typing import AnyArrayLike, Scalar, T
 from pandas.compat.numpy import _np_version_under1p17
 
 from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
@@ -24,7 +23,12 @@
     is_extension_array_dtype,
     is_integer,
 )
-from pandas.core.dtypes.generic import ABCIndex, ABCIndexClass, ABCSeries
+from pandas.core.dtypes.generic import (
+    ABCExtensionArray,
+    ABCIndex,
+    ABCIndexClass,
+    ABCSeries,
+)
 from pandas.core.dtypes.inference import _iterable_not_string
 from pandas.core.dtypes.missing import isna, isnull, notnull  # noqa
 
@@ -367,12 +371,12 @@ def standardize_mapping(into):
     Series.to_dict
     """
     if not inspect.isclass(into):
-        if isinstance(into, collections.defaultdict):
-            return partial(collections.defaultdict, into.default_factory)
+        if isinstance(into, defaultdict):
+            return partial(defaultdict, into.default_factory)
         into = type(into)
     if not issubclass(into, abc.Mapping):
         raise TypeError(f"unsupported type: {into}")
-    elif into == collections.defaultdict:
+    elif into == defaultdict:
         raise TypeError("to_dict() only accepts initialized defaultdicts")
     return into
 
@@ -473,3 +477,18 @@ def f(x):
         f = mapper
 
     return f
+
+
+def convert_to_list_like(
+    values: Union[Scalar, Iterable, AnyArrayLike]
+) -> Union[List, AnyArrayLike]:
+    """
+    Convert list-like or scalar input to list-like. List, numpy and pandas array-like
+    inputs are returned unmodified whereas others are converted to list.
+    """
+    if isinstance(values, (list, np.ndarray, ABCIndex, ABCSeries, ABCExtensionArray)):
+        return values
+    elif isinstance(values, abc.Iterable) and not isinstance(values, str):
+        return list(values)
+
+    return [values]