TST: GH20676 Verify equals operator for list of Numpy arrays

pandas/tests/generic/test_generic.py

@@ -8,7 +8,7 @@
 from pandas.core.dtypes.common import is_scalar
 
 import pandas as pd
-from pandas import DataFrame, MultiIndex, Series, date_range
+from pandas import DataFrame, Series, date_range
 import pandas._testing as tm
 import pandas.core.common as com
 
@@ -785,26 +785,6 @@ def test_depr_take_kwarg_is_copy(self, is_copy):
             s.take([0, 1], is_copy=is_copy)
 
     def test_equals(self):
-        s1 = pd.Series([1, 2, 3], index=[0, 2, 1])
-        s2 = s1.copy()
-        assert s1.equals(s2)
-
-        s1[1] = 99
-        assert not s1.equals(s2)
-
-        # NaNs compare as equal
-        s1 = pd.Series([1, np.nan, 3, np.nan], index=[0, 2, 1, 3])
-        s2 = s1.copy()
-        assert s1.equals(s2)
-
-        s2[0] = 9.9
-        assert not s1.equals(s2)
-
-        idx = MultiIndex.from_tuples([(0, "a"), (1, "b"), (2, "c")])
-        s1 = Series([1, 2, np.nan], index=idx)
-        s2 = s1.copy()
-        assert s1.equals(s2)
-
         # Add object dtype column with nans
         index = np.random.random(10)
         df1 = DataFrame(np.random.random(10), index=index, columns=["floats"])
@@ -857,21 +837,6 @@ def test_equals(self):
         df2 = df1.set_index(["floats"], append=True)
         assert df3.equals(df2)
 
-        # GH 8437
-        a = pd.Series([False, np.nan])
-        b = pd.Series([False, np.nan])
-        c = pd.Series(index=range(2), dtype=object)
-        d = c.copy()
-        e = c.copy()
-        f = c.copy()
-        c[:-1] = d[:-1] = e[0] = f[0] = False
-        assert a.equals(a)
-        assert a.equals(b)
-        assert a.equals(c)
-        assert a.equals(d)
-        assert a.equals(e)
-        assert e.equals(f)
-
     def test_pipe(self):
         df = DataFrame({"A": [1, 2, 3]})
         f = lambda x, y: x ** y

pandas/tests/series/methods/test_equals.py

@@ -0,0 +1,55 @@
+import numpy as np
+import pytest
+
+from pandas import MultiIndex, Series
+
+
+@pytest.mark.parametrize(
+    "arr, idx",
+    [
+        ([1, 2, 3, 4], [0, 2, 1, 3]),
+        ([1, np.nan, 3, np.nan], [0, 2, 1, 3]),
+        (
+            [1, np.nan, 3, np.nan],
+            MultiIndex.from_tuples([(0, "a"), (1, "b"), (2, "c"), (3, "c")]),
+        ),
+    ],
+)
+def test_equals(arr, idx):
+    s1 = Series(arr, index=idx)
+    s2 = s1.copy()
+    assert s1.equals(s2)
+
+    s1[1] = 9
+    assert not s1.equals(s2)
+
+
+def test_equals_list_array():
+    # GH20676 Verify equals operator for list of Numpy arrays
+    arr = np.array([1, 2])
+    s1 = Series([arr, arr])
+    s2 = s1.copy()
+    assert s1.equals(s2)
+
+    # TODO: Series equals should also work between single value and list
+    # s1[1] = 9
+    # assert not s1.equals(s2)
+
+
+def test_equals_false_negative():
+    # GH8437 Verify false negative behavior of equals function for dtype object
+    arr = [False, np.nan]
+    s1 = Series(arr)
+    s2 = s1.copy()
+    s3 = Series(index=range(2), dtype=object)
+    s4 = s3.copy()
+    s5 = s3.copy()
+    s6 = s3.copy()
+
+    s3[:-1] = s4[:-1] = s5[0] = s6[0] = False
+    assert s1.equals(s1)
+    assert s1.equals(s2)
+    assert s1.equals(s3)
+    assert s1.equals(s4)
+    assert s1.equals(s5)
+    assert s5.equals(s6)