Updated the docs and the error message to be more idiomatic.

Author: MJafarMashhadi

doc/source/whatsnew/v1.1.0.rst

@@ -1121,7 +1121,7 @@ Other
 - :class:`IntegerArray` now implements the ``sum`` operation (:issue:`33172`)
 - Bug in :class:`Tick` comparisons raising ``TypeError`` when comparing against timedelta-like objects (:issue:`34088`)
 - Bug in :class:`Tick` multiplication raising ``TypeError`` when multiplying by a float (:issue:`34486`)
-- Passing a `set` as `names` argument to :func:`pandas.read_csv`, :func:`pandas.read_table`, or :func:`pandas.read_fwf` will raise ``ValueError: Names should have consistent ordering. Consider a list instead.`` (:issue:`34946`)
+- Passing a `set` as `names` argument to :func:`pandas.read_csv`, :func:`pandas.read_table`, or :func:`pandas.read_fwf` will raise ``ValueError: Names should be an ordered collection.`` (:issue:`34946`)
 
 .. ---------------------------------------------------------------------------
 

pandas/io/parsers.py

@@ -408,15 +408,13 @@ def _validate_names(names):
     Raises
     ------
     ValueError
-        If names are not unique or have inconsistent ordering (e.g. set).
+        If names are not unique or are not ordered (e.g. set).
     """
     if names is not None:
         if len(names) != len(set(names)):
             raise ValueError("Duplicate names are not allowed.")
         if not is_list_like(names, allow_sets=False):
-            raise ValueError(
-                "Names should have consistent ordering. Consider a list instead."
-            )
+            raise ValueError("Names should be an ordered collection.")
 
 
 def _read(filepath_or_buffer: FilePathOrBuffer, kwds):

pandas/tests/io/parser/test_common.py

@@ -2145,7 +2145,7 @@ def test_read_csv_names_types(all_parsers):
     7,8,9
     10,11,12\n"""
     parser = all_parsers
-    msg = "Names should have consistent ordering. Consider a list instead."
+    msg = "Names should be an ordered collection."
     names = "QAZ"
     with pytest.raises(ValueError, match=msg):
         parser.read_csv(StringIO(data), names=set(names))