Fix styling of DataFrame for columns with boolean label

pandas/io/formats/style.py

@@ -2977,6 +2977,9 @@ def hide(
     # A collection of "builtin" styles
     # -----------------------------------------------------------------------
 
+    def _get_subset_default(self):
+        return self.data.columns.isin(self.data.select_dtypes(include=np.number))
+
     @doc(
         name="background",
         alt="text",
@@ -3120,7 +3123,7 @@ def background_gradient(
         .. figure:: ../../_static/style/{image_prefix}_axNone_gmap.png
         """
         if subset is None and gmap is None:
-            subset = self.data.select_dtypes(include=np.number).columns
+            subset = self._get_subset_default()
 
         self.apply(
             _background_gradient,
@@ -3155,7 +3158,7 @@ def text_gradient(
         gmap: Sequence | None = None,
     ) -> Styler:
         if subset is None and gmap is None:
-            subset = self.data.select_dtypes(include=np.number).columns
+            subset = self._get_subset_default()
 
         return self.apply(
             _background_gradient,
@@ -3308,7 +3311,7 @@ def bar(
             raise ValueError(f"`height` must be a value in [0, 100], got {height}")
 
         if subset is None:
-            subset = self.data.select_dtypes(include=np.number).columns
+            subset = self._get_subset_default()
 
         self.apply(
             _bar,

pandas/tests/io/formats/style/test_style.py

@@ -1,4 +1,5 @@
 import copy
+from itertools import combinations
 import re
 from textwrap import dedent
 
@@ -461,6 +462,31 @@ def test_apply_map_header_raises(mi_styler):
         mi_styler.applymap_index(lambda v: "attr: val;", axis="bad")._compute()
 
 
+def _gen_test_cases_subset_defaults(df_test_subset_defaults, styled_cols_expected):
+    "generate list of test cases from all subsets of columns of `df`"
+    # Iterate over all possible column in df
+    for n_cols in range(1, df_test_subset_defaults.shape[1] + 1):
+        for input_cols in combinations(df_test_subset_defaults.columns, n_cols):
+            # Use 'isin' to work around the difficulty with indexing
+            # when a column label is boolean
+            df_test_case = df_test_subset_defaults.loc[
+                :, df_test_subset_defaults.columns.isin(input_cols)
+            ]
+            styled_cols_expected_subset = list(
+                set(styled_cols_expected).intersection(df_test_case)
+            )
+
+            styled_elements_expected = {
+                (i, j)
+                for i in range(df_test_case.shape[0])
+                for j in np.where(
+                    df_test_case.columns.isin(styled_cols_expected_subset)
+                )[0]
+            }
+
+            yield df_test_case, styled_elements_expected
+
+
 class TestStyler:
     def test_init_non_pandas(self):
         msg = "``data`` must be a Series or DataFrame"
@@ -645,6 +671,46 @@ def test_apply_dataframe_return(self, index, columns):
         assert (result[(1, 0)] == [("color", "red")]) is columns  # (Y,X) only if cols
         assert (result[(0, 0)] == [("color", "red")]) is (index and columns)  # (X,X)
 
+    @pytest.mark.parametrize(
+        # styled_elements_expected is a set of tuples (i, j) with integer indices,
+        # where we expect .ctx to be set after calling _compute on the styler
+        "df_test_case, styled_elements_expected",
+        (
+            list(
+                _gen_test_cases_subset_defaults(
+                    DataFrame(
+                        {
+                            True: [1, 2],
+                            False: [3, 4],
+                            "num_column": [5, 6],
+                            "non_num_column": ["a", "b"],
+                        }
+                    ),
+                    [True, False, "num_column"],
+                )
+            )
+            + list(
+                _gen_test_cases_subset_defaults(
+                    DataFrame(
+                        {
+                            True: ["a", "b"],
+                            False: [3, 4],
+                            "num_column": [5, 6],
+                        }
+                    ),
+                    [False, "num_column"],
+                )
+            )
+        ),
+    )
+    @pytest.mark.parametrize(
+        "stylefunc", ["background_gradient", "bar", "text_gradient"]
+    )
+    def test_subset_defaults(self, df_test_case, styled_elements_expected, stylefunc):
+        styled = getattr(df_test_case.style, stylefunc)()
+        styled._compute()
+        assert set(styled.ctx) == set(styled_elements_expected)
+
     @pytest.mark.parametrize(
         "slice_",
         [