diff --git a/pandas/tests/groupby/test_function.py b/pandas/tests/groupby/test_function.py
index c402ca194648f..83080aa98648f 100644
--- a/pandas/tests/groupby/test_function.py
+++ b/pandas/tests/groupby/test_function.py
@@ -1,7 +1,6 @@
 import builtins
 import datetime as dt
 from io import StringIO
-from itertools import product
 from string import ascii_lowercase
 
 import numpy as np
@@ -1296,36 +1295,32 @@ def __eq__(self, other):
 # --------------------------------
 
 
-def test_size(df):
-    grouped = df.groupby(["A", "B"])
+@pytest.mark.parametrize("by", ["A", "B", ["A", "B"]])
+def test_size(df, by):
+    grouped = df.groupby(by=by)
     result = grouped.size()
     for key, group in grouped:
         assert result[key] == len(group)
 
-    grouped = df.groupby("A")
-    result = grouped.size()
-    for key, group in grouped:
-        assert result[key] == len(group)
 
-    grouped = df.groupby("B")
-    result = grouped.size()
-    for key, group in grouped:
-        assert result[key] == len(group)
+@pytest.mark.parametrize("by", ["A", "B", ["A", "B"]])
+@pytest.mark.parametrize("sort", [True, False])
+def test_size_sort(df, sort, by):
+    df = DataFrame(np.random.choice(20, (1000, 3)), columns=list("ABC"))
+    left = df.groupby(by=by, sort=sort).size()
+    right = df.groupby(by=by, sort=sort)["C"].apply(lambda a: a.shape[0])
+    tm.assert_series_equal(left, right, check_names=False)
 
-    df = DataFrame(np.random.choice(20, (1000, 3)), columns=list("abc"))
-    for sort, key in product((False, True), ("a", "b", ["a", "b"])):
-        left = df.groupby(key, sort=sort).size()
-        right = df.groupby(key, sort=sort)["c"].apply(lambda a: a.shape[0])
-        tm.assert_series_equal(left, right, check_names=False)
 
-    # GH11699
+def test_size_series_dataframe():
+    # https://github.com/pandas-dev/pandas/issues/11699
     df = DataFrame(columns=["A", "B"])
     out = Series(dtype="int64", index=Index([], name="A"))
     tm.assert_series_equal(df.groupby("A").size(), out)
 
 
 def test_size_groupby_all_null():
-    # GH23050
+    # https://github.com/pandas-dev/pandas/issues/23050
     # Assert no 'Value Error : Length of passed values is 2, index implies 0'
     df = DataFrame({"A": [None, None]})  # all-null groups
     result = df.groupby("A").size()
@@ -1335,6 +1330,8 @@ def test_size_groupby_all_null():
 
 # quantile
 # --------------------------------
+
+
 @pytest.mark.parametrize(
     "interpolation", ["linear", "lower", "higher", "nearest", "midpoint"]
 )