BUG: constructing a DataFrame using range doesn't work

doc/source/whatsnew/v0.25.0.rst

@@ -415,6 +415,7 @@ Reshaping
 - Bug in :func:`pivot_table` where columns with ``NaN`` values are dropped even if ``dropna`` argument is ``False``, when the ``aggfunc`` argument contains a ``list`` (:issue:`22159`)
 - Bug in :func:`concat` where the resulting ``freq`` of two :class:`DatetimeIndex` with the same ``freq`` would be dropped (:issue:`3232`).
 - Bug in :func:`merge` where merging with equivalent Categorical dtypes was raising an error (:issue:`22501`)
+- bug in :class:`DataFrame` instantiating with a ``range`` (e.g. ``pd.DataFrame(range(3))``) raised an error (:issue:`26342`).
 - Bug in :class:`DataFrame` constructor when passing non-empty tuples would cause a segmentation fault (:issue:`25691`)
 - Bug in :func:`pandas.cut` where large bins could incorrectly raise an error due to an integer overflow (:issue:`26045`)
 - Bug in :func:`DataFrame.sort_index` where an error is thrown when a multi-indexed DataFrame is sorted on all levels with the initial level sorted last (:issue:`26053`)

pandas/core/dtypes/cast.py

@@ -35,8 +35,8 @@
 def maybe_convert_platform(values):
     """ try to do platform conversion, allow ndarray or list here """
 
-    if isinstance(values, (list, tuple)):
-        values = construct_1d_object_array_from_listlike(list(values))
+    if isinstance(values, (list, tuple, range)):
+        values = construct_1d_object_array_from_listlike(values)
     if getattr(values, 'dtype', None) == np.object_:
         if hasattr(values, '_values'):
             values = values._values

pandas/tests/frame/test_constructors.py

@@ -33,11 +33,13 @@ class TestDataFrameConstructors(TestData):
         lambda: DataFrame(()),
         lambda: DataFrame([]),
         lambda: DataFrame((x for x in [])),
+        lambda: DataFrame(range(0)),
         lambda: DataFrame(data=None),
         lambda: DataFrame(data={}),
         lambda: DataFrame(data=()),
         lambda: DataFrame(data=[]),
-        lambda: DataFrame(data=(x for x in []))
+        lambda: DataFrame(data=(x for x in [])),
+        lambda: DataFrame(data=range(0)),
     ])
     def test_empty_constructor(self, constructor):
         expected = DataFrame()
@@ -999,6 +1001,17 @@ def __len__(self, n):
                             array.array('i', range(10))])
         tm.assert_frame_equal(result, expected, check_dtype=False)
 
+    def test_constructor_range(self):
+        # GH26342
+        result = DataFrame(range(10))
+        expected = DataFrame(list(range(10)))
+        tm.assert_frame_equal(result, expected)
+
+    def test_constructor_list_of_ranges(self):
+        result = DataFrame([range(10), range(10)])
+        expected = DataFrame([list(range(10)), list(range(10))])
+        tm.assert_frame_equal(result, expected)
+
     def test_constructor_iterable(self):
         # GH 21987
         class Iter:
@@ -1011,9 +1024,13 @@ def __iter__(self):
         tm.assert_frame_equal(result, expected)
 
     def test_constructor_iterator(self):
+        result = DataFrame(iter(range(10)))
+        expected = DataFrame(list(range(10)))
+        tm.assert_frame_equal(result, expected)
 
+    def test_constructor_list_of_iterators(self):
+        result = DataFrame([iter(range(10)), iter(range(10))])
         expected = DataFrame([list(range(10)), list(range(10))])
-        result = DataFrame([range(10), range(10)])
         tm.assert_frame_equal(result, expected)
 
     def test_constructor_generator(self):
@@ -2251,8 +2268,13 @@ def test_to_frame_with_falsey_names(self):
 
     @pytest.mark.parametrize('dtype', [None, 'uint8', 'category'])
     def test_constructor_range_dtype(self, dtype):
-        # GH 16804
         expected = DataFrame({'A': [0, 1, 2, 3, 4]}, dtype=dtype or 'int64')
+
+        # GH 26342
+        result = DataFrame(range(5), columns=['A'], dtype=dtype)
+        tm.assert_frame_equal(result, expected)
+
+        # GH 16804
         result = DataFrame({'A': range(5)}, dtype=dtype)
         tm.assert_frame_equal(result, expected)