From 20ed975b1eb5affe3295517926428ae31b949af1 Mon Sep 17 00:00:00 2001
From: Richard Shadrach <rhshadrach@gmail.com>
Date: Mon, 18 Oct 2021 13:47:29 -0400
Subject: [PATCH] BUG: crosstab fails with lists/tuples

---
 doc/source/whatsnew/v1.4.0.rst        |  1 +
 pandas/core/reshape/pivot.py          |  7 +++++--
 pandas/tests/reshape/test_crosstab.py | 18 +++++++++++-------
 3 files changed, 17 insertions(+), 9 deletions(-)

diff --git a/doc/source/whatsnew/v1.4.0.rst b/doc/source/whatsnew/v1.4.0.rst
index b7efec8fd2e89..0f2102b70653a 100644
--- a/doc/source/whatsnew/v1.4.0.rst
+++ b/doc/source/whatsnew/v1.4.0.rst
@@ -545,6 +545,7 @@ Reshaping
 - Bug in :func:`crosstab` when inputs are are categorical Series, there are categories that are not present in one or both of the Series, and ``margins=True``. Previously the margin value for missing categories was ``NaN``. It is now correctly reported as 0 (:issue:`43505`)
 - Bug in :func:`concat` would fail when the ``objs`` argument all had the same index and the ``keys`` argument contained duplicates (:issue:`43595`)
 - Bug in :func:`concat` which ignored the ``sort`` parameter (:issue:`43375`)
+- Bug in :func:`crosstab` would fail when inputs are lists or tuples (:issue:`44076`)
 
 Sparse
 ^^^^^^
diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index fcf00276aa8af..edd3599aabe35 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -25,6 +25,7 @@
 from pandas.core.dtypes.common import (
     is_integer_dtype,
     is_list_like,
+    is_nested_list_like,
     is_scalar,
 )
 from pandas.core.dtypes.generic import (
@@ -625,8 +626,10 @@ def crosstab(
     if values is not None and aggfunc is None:
         raise ValueError("values cannot be used without an aggfunc.")
 
-    index = com.maybe_make_list(index)
-    columns = com.maybe_make_list(columns)
+    if not is_nested_list_like(index):
+        index = [index]
+    if not is_nested_list_like(columns):
+        columns = [columns]
 
     common_idx = None
     pass_objs = [x for x in index + columns if isinstance(x, (ABCSeries, ABCDataFrame))]
diff --git a/pandas/tests/reshape/test_crosstab.py b/pandas/tests/reshape/test_crosstab.py
index f252b5e1ceedf..74beda01e4b8a 100644
--- a/pandas/tests/reshape/test_crosstab.py
+++ b/pandas/tests/reshape/test_crosstab.py
@@ -84,10 +84,12 @@ def test_crosstab_multiple(self):
         expected = expected.unstack("A").fillna(0).astype(np.int64)
         tm.assert_frame_equal(result, expected)
 
-    def test_crosstab_ndarray(self):
-        a = np.random.randint(0, 5, size=100)
-        b = np.random.randint(0, 3, size=100)
-        c = np.random.randint(0, 10, size=100)
+    @pytest.mark.parametrize("box", [np.array, list, tuple])
+    def test_crosstab_ndarray(self, box):
+        # GH 44076
+        a = box(np.random.randint(0, 5, size=100))
+        b = box(np.random.randint(0, 3, size=100))
+        c = box(np.random.randint(0, 10, size=100))
 
         df = DataFrame({"a": a, "b": b, "c": c})
 
@@ -100,9 +102,11 @@ def test_crosstab_ndarray(self):
         tm.assert_frame_equal(result, expected)
 
         # assign arbitrary names
-        result = crosstab(self.df["A"].values, self.df["C"].values)
-        assert result.index.name == "row_0"
-        assert result.columns.name == "col_0"
+        result = crosstab(a, c)
+        expected = crosstab(df["a"], df["c"])
+        expected.index.names = ["row_0"]
+        expected.columns.names = ["col_0"]
+        tm.assert_frame_equal(result, expected)
 
     def test_crosstab_non_aligned(self):
         # GH 17005