BUG: Support to create DataFrame from list subclasses.

Issue: #21226

Author: mitar

asv_bench/benchmarks/frame_ctor.py

@@ -99,3 +99,16 @@ def setup(self):
 
     def time_frame_from_ndarray(self):
         self.df = DataFrame(self.data)
+
+
+class FromLists(object):
+
+    goal_time = 0.2
+
+    def setup(self):
+        N = 1000
+        M = 100
+        self.data = [[j for j in range(M)] for i in range(N)]
+
+    def time_frame_from_lists(self):
+        self.df = DataFrame(self.data)

doc/source/whatsnew/v0.23.1.txt

@@ -70,8 +70,7 @@ Categorical
 Conversion
 ^^^^^^^^^^
 
--
--
+- Bug in :func:`to_object_array` prevented list subclasses to be used to create :class:`DataFrame` (:issue:`21226`)
 
 Indexing
 ^^^^^^^^

pandas/_libs/src/inference.pyx

@@ -1487,7 +1487,7 @@ def map_infer(ndarray arr, object f, bint convert=1):
     return result
 
 
-def to_object_array(list rows, int min_width=0):
+def to_object_array(rows, int min_width=0):
     """
     Convert a list of lists into an object array.
 
@@ -1508,20 +1508,22 @@ def to_object_array(list rows, int min_width=0):
     cdef:
         Py_ssize_t i, j, n, k, tmp
         ndarray[object, ndim=2] result
+        list input_rows
         list row
 
-    n = len(rows)
+    input_rows = <list>rows
+    n = len(input_rows)
 
     k = min_width
     for i from 0 <= i < n:
-        tmp = len(rows[i])
+        tmp = len(input_rows[i])
         if tmp > k:
             k = tmp
 
     result = np.empty((n, k), dtype=object)
 
     for i from 0 <= i < n:
-        row = rows[i]
+        row = <list>input_rows[i]
 
         for j from 0 <= j < len(row):
             result[i, j] = row[j]

pandas/tests/frame/test_constructors.py

@@ -2149,6 +2149,15 @@ def test_constructor_range_dtype(self, dtype):
         result = DataFrame({'A': range(5)}, dtype=dtype)
         tm.assert_frame_equal(result, expected)
 
+    def test_frame_from_list_subclass(self):
+        # GH21226
+        class List(list):
+            pass
+
+        expected = DataFrame([[1, 2, 3], [4, 5, 6]])
+        result = DataFrame(List([List([1, 2, 3]), List([4, 5, 6])]))
+        tm.assert_frame_equal(result, expected)
+
 
 class TestDataFrameConstructorWithDatetimeTZ(TestData):