BUG: Ensure df.itertuples() uses plain tuples correctly

Currently DataFrame.itertuples() has an off by one error
when it inspects whether or not it should return namedtuples
or plain tuples in it's response.

This PR addresses that bug by correcting the condition
that is used when making the check.

Closes: pandas-dev#28282

Author: simongibbons

doc/source/whatsnew/v1.0.0.rst

@@ -987,6 +987,7 @@ Other
 - Bug in :class:`Index` where a non-hashable name could be set without raising ``TypeError`` (:issue:`29069`)
 - Bug in :class:`DataFrame` constructor when passing a 2D ``ndarray`` and an extension dtype (:issue:`12513`)
 - Bug in :meth:`DaataFrame.to_csv` when supplied a series with a ``dtype="string"`` and a ``na_rep``, the ``na_rep`` was being truncated to 2 characters. (:issue:`29975`)
+- Bug where :meth:`DataFrame.itertuples` would incorrectly determine whether or not namedtuples could be used for dataframes of 255 columns (:issue:`28282`)
 
 .. _whatsnew_1000.contributors:
 

pandas/core/frame.py

@@ -1018,8 +1018,8 @@ def itertuples(self, index=True, name="Pandas"):
         # use integer indexing because of possible duplicate column names
         arrays.extend(self.iloc[:, k] for k in range(len(self.columns)))
 
-        # Python 3 supports at most 255 arguments to constructor
-        if name is not None and len(self.columns) + index < 256:
+        # Python versions before 3.7 support at most 255 arguments to constructor
+        if name is not None and len(self.columns) + index < 255:
             itertuple = collections.namedtuple(name, fields, rename=True)
             return map(itertuple._make, zip(*arrays))
 

pandas/tests/frame/test_api.py

@@ -288,6 +288,22 @@ def test_sequence_like_with_categorical(self):
         for c, col in df.items():
             str(s)
 
+    def test_itertuples_fallback_to_regular_tuples(self):
+        # GH 28282
+
+        df_254_columns = DataFrame([{f"foo_{i}": f"bar_{i}" for i in range(254)}])
+        result_254_columns = next(df_254_columns.itertuples(index=False))
+        assert isinstance(result_254_columns, tuple)
+        assert result_254_columns.foo_1 == "bar_1"
+
+        df_255_columns = DataFrame([{f"foo_{i}": f"bar_{i}" for i in range(255)}])
+        result_255_columns = next(df_255_columns.itertuples(index=False))
+        assert isinstance(result_255_columns, tuple)
+
+        # Dataframes with >=255 columns will fallback to regular tuples
+        with pytest.raises(AttributeError):
+            result_255_columns.foo_1
+
     def test_len(self, float_frame):
         assert len(float_frame) == len(float_frame.index)