BUG: Subset slicer on Styler failed on MultiIndex with slice(None) (#39421)

Author: attack68

doc/source/whatsnew/v1.3.0.rst

@@ -438,6 +438,8 @@ Other
 - Bug in :class:`Styler` which caused CSS to duplicate on multiple renders. (:issue:`39395`)
 - :meth:`Index.where` behavior now mirrors :meth:`Index.putmask` behavior, i.e. ``index.where(mask, other)`` matches ``index.putmask(~mask, other)`` (:issue:`39412`)
 - Bug in :func:`pandas.testing.assert_series_equal`, :func:`pandas.testing.assert_frame_equal`, :func:`pandas.testing.assert_index_equal` and :func:`pandas.testing.assert_extension_array_equal` incorrectly raising when an attribute has an unrecognized NA type (:issue:`39461`)
+- Bug in :class:`Styler` where ``subset`` arg in methods raised an error for some valid multiindex slices (:issue:`33562`)
+-
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/indexing.py

@@ -2407,9 +2407,11 @@ def pred(part) -> bool:
         """
         # true when slice does *not* reduce, False when part is a tuple,
         # i.e. MultiIndex slice
-        return (isinstance(part, slice) or is_list_like(part)) and not isinstance(
-            part, tuple
-        )
+        if isinstance(part, tuple):
+            # GH#39421 check for sub-slice:
+            return any((isinstance(s, slice) or is_list_like(s)) for s in part)
+        else:
+            return isinstance(part, slice) or is_list_like(part)
 
     if not is_list_like(slice_):
         if not isinstance(slice_, slice):

pandas/tests/indexing/multiindex/test_slice.py

@@ -780,6 +780,42 @@ def test_non_reducing_slice_on_multiindex(self):
         expected = DataFrame({("b", "d"): [4, 1]})
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize(
+        "slice_",
+        [
+            pd.IndexSlice[:, :],
+            # check cols
+            pd.IndexSlice[:, pd.IndexSlice[["a"]]],  # inferred deeper need list
+            pd.IndexSlice[:, pd.IndexSlice[["a"], ["c"]]],  # inferred deeper need list
+            pd.IndexSlice[:, pd.IndexSlice["a", "c", :]],
+            pd.IndexSlice[:, pd.IndexSlice["a", :, "e"]],
+            pd.IndexSlice[:, pd.IndexSlice[:, "c", "e"]],
+            pd.IndexSlice[:, pd.IndexSlice["a", ["c", "d"], :]],  # check list
+            pd.IndexSlice[:, pd.IndexSlice["a", ["c", "d", "-"], :]],  # allow missing
+            pd.IndexSlice[:, pd.IndexSlice["a", ["c", "d", "-"], "e"]],  # no slice
+            # check rows
+            pd.IndexSlice[pd.IndexSlice[["U"]], :],  # inferred deeper need list
+            pd.IndexSlice[pd.IndexSlice[["U"], ["W"]], :],  # inferred deeper need list
+            pd.IndexSlice[pd.IndexSlice["U", "W", :], :],
+            pd.IndexSlice[pd.IndexSlice["U", :, "Y"], :],
+            pd.IndexSlice[pd.IndexSlice[:, "W", "Y"], :],
+            pd.IndexSlice[pd.IndexSlice[:, "W", ["Y", "Z"]], :],  # check list
+            pd.IndexSlice[pd.IndexSlice[:, "W", ["Y", "Z", "-"]], :],  # allow missing
+            pd.IndexSlice[pd.IndexSlice["U", "W", ["Y", "Z", "-"]], :],  # no slice
+            # check simultaneous
+            pd.IndexSlice[pd.IndexSlice[:, "W", "Y"], pd.IndexSlice["a", "c", :]],
+        ],
+    )
+    def test_non_reducing_multi_slice_on_multiindex(self, slice_):
+        # GH 33562
+        cols = pd.MultiIndex.from_product([["a", "b"], ["c", "d"], ["e", "f"]])
+        idxs = pd.MultiIndex.from_product([["U", "V"], ["W", "X"], ["Y", "Z"]])
+        df = DataFrame(np.arange(64).reshape(8, 8), columns=cols, index=idxs)
+
+        expected = df.loc[slice_]
+        result = df.loc[non_reducing_slice(slice_)]
+        tm.assert_frame_equal(result, expected)
+
     def test_loc_slice_negative_stepsize(self):
         # GH#38071
         mi = MultiIndex.from_product([["a", "b"], [0, 1]])

pandas/tests/io/formats/test_style.py

@@ -377,29 +377,26 @@ def f(x):
             }
             assert result == expected
 
-    def test_applymap_subset_multiindex(self):
+    @pytest.mark.parametrize(
+        "slice_",
+        [
+            pd.IndexSlice[:, pd.IndexSlice["x", "A"]],
+            pd.IndexSlice[:, pd.IndexSlice[:, "A"]],
+            pd.IndexSlice[:, pd.IndexSlice[:, ["A", "C"]]],  # missing col element
+            pd.IndexSlice[pd.IndexSlice["a", 1], :],
+            pd.IndexSlice[pd.IndexSlice[:, 1], :],
+            pd.IndexSlice[pd.IndexSlice[:, [1, 3]], :],  # missing row element
+            pd.IndexSlice[:, ("x", "A")],
+            pd.IndexSlice[("a", 1), :],
+        ],
+    )
+    def test_applymap_subset_multiindex(self, slice_):
         # GH 19861
-        # Smoke test for applymap
-        def color_negative_red(val):
-            """
-            Takes a scalar and returns a string with
-            the css property `'color: red'` for negative
-            strings, black otherwise.
-            """
-            color = "red" if val < 0 else "black"
-            return f"color: {color}"
-
-        dic = {
-            ("a", "d"): [-1.12, 2.11],
-            ("a", "c"): [2.78, -2.88],
-            ("b", "c"): [-3.99, 3.77],
-            ("b", "d"): [4.21, -1.22],
-        }
-
-        idx = pd.IndexSlice
-        df = DataFrame(dic, index=[0, 1])
-
-        (df.style.applymap(color_negative_red, subset=idx[:, idx["b", "d"]]).render())
+        # edited for GH 33562
+        idx = pd.MultiIndex.from_product([["a", "b"], [1, 2]])
+        col = pd.MultiIndex.from_product([["x", "y"], ["A", "B"]])
+        df = DataFrame(np.random.rand(4, 4), columns=col, index=idx)
+        df.style.applymap(lambda x: "color: red;", subset=slice_).render()
 
     def test_applymap_subset_multiindex_code(self):
         # https://github.com/pandas-dev/pandas/issues/25858