diff --git a/pandas/tests/io/formats/style/test_align.py b/pandas/tests/io/formats/style/test_align.py
index be7d2fc3be518..7451d9d2369ab 100644
--- a/pandas/tests/io/formats/style/test_align.py
+++ b/pandas/tests/io/formats/style/test_align.py
@@ -23,258 +23,20 @@ def no_bar():
     return bar_grad()
 
 
-def bar_to(x):
-    return bar_grad(f" #d65f5f {x:.1f}%", f" transparent {x:.1f}%")
+def bar_to(x, color="#d65f5f"):
+    return bar_grad(f" {color} {x:.1f}%", f" transparent {x:.1f}%")
 
 
-def bar_from_to(x, y):
+def bar_from_to(x, y, color="#d65f5f"):
     return bar_grad(
         f" transparent {x:.1f}%",
-        f" #d65f5f {x:.1f}%",
-        f" #d65f5f {y:.1f}%",
+        f" {color} {x:.1f}%",
+        f" {color} {y:.1f}%",
         f" transparent {y:.1f}%",
     )
 
 
 class TestStylerBarAlign:
-    def test_bar_align_left(self):
-        df = DataFrame({"A": [0, 1, 2]})
-        result = df.style.bar(align="left")._compute().ctx
-        expected = {
-            (0, 0): bar_grad(),
-            (1, 0): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
-            (2, 0): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
-        }
-        assert result == expected
-
-        result = df.style.bar(color="red", width=50, align="left")._compute().ctx
-        expected = {
-            (0, 0): bar_grad(),
-            (1, 0): bar_grad(" red 25.0%", " transparent 25.0%"),
-            (2, 0): bar_grad(" red 50.0%", " transparent 50.0%"),
-        }
-        assert result == expected
-
-        df["C"] = ["a"] * len(df)
-        result = df.style.bar(color="red", width=50, align="left")._compute().ctx
-        assert result == expected
-        df["C"] = df["C"].astype("category")
-        result = df.style.bar(color="red", width=50, align="left")._compute().ctx
-        assert result == expected
-
-    def test_bar_align_left_0points(self):
-        df = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
-        result = df.style.bar(align="left")._compute().ctx
-        expected = {
-            (0, 0): bar_grad(),
-            (0, 1): bar_grad(),
-            (0, 2): bar_grad(),
-            (1, 0): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
-            (1, 1): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
-            (1, 2): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
-            (2, 0): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
-            (2, 1): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
-            (2, 2): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
-        }
-        assert result == expected
-
-        result = df.style.bar(axis=1, align="left")._compute().ctx
-        expected = {
-            (0, 0): bar_grad(),
-            (0, 1): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
-            (0, 2): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
-            (1, 0): bar_grad(),
-            (1, 1): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
-            (1, 2): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
-            (2, 0): bar_grad(),
-            (2, 1): bar_grad(" #d65f5f 50.0%", " transparent 50.0%"),
-            (2, 2): bar_grad(" #d65f5f 100.0%", " transparent 100.0%"),
-        }
-        assert result == expected
-
-    def test_bar_align_mid_pos_and_neg(self):
-        df = DataFrame({"A": [-10, 0, 20, 90]})
-        result = df.style.bar(align="mid", color=["#d65f5f", "#5fba7d"])._compute().ctx
-        expected = {
-            (0, 0): bar_grad(
-                " #d65f5f 10.0%",
-                " transparent 10.0%",
-            ),
-            (1, 0): bar_grad(),
-            (2, 0): bar_grad(
-                " transparent 10.0%",
-                " #5fba7d 10.0%",
-                " #5fba7d 30.0%",
-                " transparent 30.0%",
-            ),
-            (3, 0): bar_grad(
-                " transparent 10.0%",
-                " #5fba7d 10.0%",
-                " #5fba7d 100.0%",
-                " transparent 100.0%",
-            ),
-        }
-        assert result == expected
-
-    def test_bar_align_mid_all_pos(self):
-        df = DataFrame({"A": [10, 20, 50, 100]})
-
-        result = df.style.bar(align="mid", color=["#d65f5f", "#5fba7d"])._compute().ctx
-
-        expected = {
-            (0, 0): bar_grad(
-                " #5fba7d 10.0%",
-                " transparent 10.0%",
-            ),
-            (1, 0): bar_grad(
-                " #5fba7d 20.0%",
-                " transparent 20.0%",
-            ),
-            (2, 0): bar_grad(
-                " #5fba7d 50.0%",
-                " transparent 50.0%",
-            ),
-            (3, 0): bar_grad(
-                " #5fba7d 100.0%",
-                " transparent 100.0%",
-            ),
-        }
-
-        assert result == expected
-
-    def test_bar_align_mid_all_neg(self):
-        df = DataFrame({"A": [-100, -60, -30, -20]})
-
-        result = df.style.bar(align="mid", color=["#d65f5f", "#5fba7d"])._compute().ctx
-
-        expected = {
-            (0, 0): bar_grad(
-                " #d65f5f 100.0%",
-                " transparent 100.0%",
-            ),
-            (1, 0): bar_grad(
-                " transparent 40.0%",
-                " #d65f5f 40.0%",
-                " #d65f5f 100.0%",
-                " transparent 100.0%",
-            ),
-            (2, 0): bar_grad(
-                " transparent 70.0%",
-                " #d65f5f 70.0%",
-                " #d65f5f 100.0%",
-                " transparent 100.0%",
-            ),
-            (3, 0): bar_grad(
-                " transparent 80.0%",
-                " #d65f5f 80.0%",
-                " #d65f5f 100.0%",
-                " transparent 100.0%",
-            ),
-        }
-        assert result == expected
-
-    def test_bar_align_zero_pos_and_neg(self):
-        # See https://github.com/pandas-dev/pandas/pull/14757
-        df = DataFrame({"A": [-10, 0, 20, 90]})
-
-        result = (
-            df.style.bar(align="zero", color=["#d65f5f", "#5fba7d"], width=90)
-            ._compute()
-            .ctx
-        )
-        expected = {
-            (0, 0): bar_grad(
-                " transparent 40.0%",
-                " #d65f5f 40.0%",
-                " #d65f5f 45.0%",
-                " transparent 45.0%",
-            ),
-            (1, 0): bar_grad(),
-            (2, 0): bar_grad(
-                " transparent 45.0%",
-                " #5fba7d 45.0%",
-                " #5fba7d 55.0%",
-                " transparent 55.0%",
-            ),
-            (3, 0): bar_grad(
-                " transparent 45.0%",
-                " #5fba7d 45.0%",
-                " #5fba7d 90.0%",
-                " transparent 90.0%",
-            ),
-        }
-        assert result == expected
-
-    def test_bar_align_left_axis_none(self):
-        df = DataFrame({"A": [0, 1], "B": [2, 4]})
-        result = df.style.bar(axis=None, align="left")._compute().ctx
-        expected = {
-            (0, 0): bar_grad(),
-            (1, 0): bar_grad(
-                " #d65f5f 25.0%",
-                " transparent 25.0%",
-            ),
-            (0, 1): bar_grad(
-                " #d65f5f 50.0%",
-                " transparent 50.0%",
-            ),
-            (1, 1): bar_grad(
-                " #d65f5f 100.0%",
-                " transparent 100.0%",
-            ),
-        }
-        assert result == expected
-
-    def test_bar_align_zero_axis_none(self):
-        df = DataFrame({"A": [0, 1], "B": [-2, 4]})
-        result = df.style.bar(align="zero", axis=None)._compute().ctx
-        expected = {
-            (0, 0): bar_grad(),
-            (1, 0): bar_grad(
-                " transparent 50.0%",
-                " #d65f5f 50.0%",
-                " #d65f5f 62.5%",
-                " transparent 62.5%",
-            ),
-            (0, 1): bar_grad(
-                " transparent 25.0%",
-                " #d65f5f 25.0%",
-                " #d65f5f 50.0%",
-                " transparent 50.0%",
-            ),
-            (1, 1): bar_grad(
-                " transparent 50.0%",
-                " #d65f5f 50.0%",
-                " #d65f5f 100.0%",
-                " transparent 100.0%",
-            ),
-        }
-        assert result == expected
-
-    def test_bar_align_mid_axis_none(self):
-        df = DataFrame({"A": [0, 1], "B": [-2, 4]})
-        result = df.style.bar(align="mid", axis=None)._compute().ctx
-        expected = {
-            (0, 0): bar_grad(),
-            (1, 0): bar_grad(
-                " transparent 33.3%",
-                " #d65f5f 33.3%",
-                " #d65f5f 50.0%",
-                " transparent 50.0%",
-            ),
-            (0, 1): bar_grad(
-                " #d65f5f 33.3%",
-                " transparent 33.3%",
-            ),
-            (1, 1): bar_grad(
-                " transparent 33.3%",
-                " #d65f5f 33.3%",
-                " #d65f5f 100.0%",
-                " transparent 100.0%",
-            ),
-        }
-        assert result == expected
-
     def test_bar_align_mid_vmin(self):
         df = DataFrame({"A": [0, 1], "B": [-2, 4]})
         result = df.style.bar(align="mid", axis=None, vmin=-6)._compute().ctx
@@ -438,7 +200,7 @@ def test_bar_bad_align_raises(self):
         (np.median, [bar_to(50), no_bar(), bar_from_to(50, 100)]),
     ],
 )
-def test_bar_align_positive_cases(align, exp):
+def test_align_positive_cases(align, exp):
     # test different align cases for all positive values
     data = DataFrame([[1], [2], [3]])
     result = data.style.bar(align=align)._compute().ctx
@@ -458,7 +220,7 @@ def test_bar_align_positive_cases(align, exp):
         (np.median, [bar_from_to(50, 100), no_bar(), bar_to(50)]),
     ],
 )
-def test_bar_align_negative_cases(align, exp):
+def test_align_negative_cases(align, exp):
     # test different align cases for all negative values
     data = DataFrame([[-1], [-2], [-3]])
     result = data.style.bar(align=align)._compute().ctx
@@ -478,9 +240,105 @@ def test_bar_align_negative_cases(align, exp):
         (np.median, [bar_to(50), no_bar(), bar_from_to(50, 62.5)]),
     ],
 )
-def test_bar_align_mixed_cases(align, exp):
+def test_align_mixed_cases(align, exp):
     # test different align cases for mixed positive and negative values
     data = DataFrame([[-3], [1], [2]])
     result = data.style.bar(align=align)._compute().ctx
     expected = {(0, 0): exp[0], (1, 0): exp[1], (2, 0): exp[2]}
     assert result == expected
+
+
+@pytest.mark.parametrize(
+    "align, exp",
+    [
+        (
+            "left",
+            {
+                "index": [[no_bar(), no_bar()], [bar_to(100), bar_to(100)]],
+                "columns": [[no_bar(), bar_to(100)], [no_bar(), bar_to(100)]],
+                "none": [[no_bar(), bar_to(33.33)], [bar_to(66.66), bar_to(100)]],
+            },
+        ),
+        (
+            "mid",
+            {
+                "index": [[bar_to(33.33), bar_to(50)], [bar_to(100), bar_to(100)]],
+                "columns": [[bar_to(50), bar_to(100)], [bar_to(75), bar_to(100)]],
+                "none": [[bar_to(25), bar_to(50)], [bar_to(75), bar_to(100)]],
+            },
+        ),
+        (
+            "zero",
+            {
+                "index": [
+                    [bar_from_to(50, 66.66), bar_from_to(50, 75)],
+                    [bar_from_to(50, 100), bar_from_to(50, 100)],
+                ],
+                "columns": [
+                    [bar_from_to(50, 75), bar_from_to(50, 100)],
+                    [bar_from_to(50, 87.5), bar_from_to(50, 100)],
+                ],
+                "none": [
+                    [bar_from_to(50, 62.5), bar_from_to(50, 75)],
+                    [bar_from_to(50, 87.5), bar_from_to(50, 100)],
+                ],
+            },
+        ),
+        (
+            2,
+            {
+                "index": [
+                    [bar_to(50), no_bar()],
+                    [bar_from_to(50, 100), bar_from_to(50, 100)],
+                ],
+                "columns": [
+                    [bar_to(50), no_bar()],
+                    [bar_from_to(50, 75), bar_from_to(50, 100)],
+                ],
+                "none": [
+                    [bar_from_to(25, 50), no_bar()],
+                    [bar_from_to(50, 75), bar_from_to(50, 100)],
+                ],
+            },
+        ),
+    ],
+)
+@pytest.mark.parametrize("axis", ["index", "columns", "none"])
+def test_align_axis(align, exp, axis):
+    # test all axis combinations with positive values and different aligns
+    data = DataFrame([[1, 2], [3, 4]])
+    result = (
+        data.style.bar(align=align, axis=None if axis == "none" else axis)
+        ._compute()
+        .ctx
+    )
+    expected = {
+        (0, 0): exp[axis][0][0],
+        (0, 1): exp[axis][0][1],
+        (1, 0): exp[axis][1][0],
+        (1, 1): exp[axis][1][1],
+    }
+    assert result == expected
+
+
+def test_numerics():
+    # test data is pre-selected for numeric values
+    data = DataFrame([[1, "a"], [2, "b"]])
+    result = data.style.bar()._compute().ctx
+    assert (0, 1) not in result
+    assert (1, 1) not in result
+
+
+@pytest.mark.parametrize(
+    "align, exp",
+    [
+        ("left", [no_bar(), bar_to(100, "green")]),
+        ("right", [bar_to(100, "red"), no_bar()]),
+        ("mid", [bar_to(25, "red"), bar_from_to(25, 100, "green")]),
+        ("zero", [bar_from_to(33.33, 50, "red"), bar_from_to(50, 100, "green")]),
+    ],
+)
+def test_colors_mixed(align, exp):
+    data = DataFrame([[-1], [3]])
+    result = data.style.bar(align=align, color=["red", "green"])._compute().ctx
+    assert result == {(0, 0): exp[0], (1, 0): exp[1]}