fix: check if int series, return current otherwise

Author: sharonwoo

pandas/plotting/_matplotlib/core.py

@@ -1805,14 +1805,9 @@ def _kind(self) -> Literal["bar", "barh"]:
     def orientation(self) -> PlottingOrientation:
         return "vertical"
 
-    # GH56460 checks similar to LinePlot's _is_ts_plot and _use_dynamic_x
-    @final
-    def _is_ts_plot(self, data) -> bool:
-        return self.use_index and use_dynamic_x(self._get_ax(0), data)
-
     @final
     def _set_tick_pos(self, data) -> np.ndarray:
-        if self._is_series and not self._is_ts_plot(data):
+        if self._is_series and is_integer_dtype(data.index):
             return np.array(self._get_xticks(), dtype=int)
         else:
             return np.arange(len(data))

pandas/tests/plotting/test_series.py

@@ -974,25 +974,31 @@ def test_series_none_color(self):
         expected = _unpack_cycler(mpl.pyplot.rcParams)[:1]
         _check_colors(ax.get_lines(), linecolors=expected)
 
-    @pytest.mark.parametrize(
-        "plot_data",
-        [
-            (
-                {
-                    "bars": {-1: 0.5, 0: 1.0, 1: 3.0, 2: 3.5, 3: 1.5},
-                    "pct": {-1: 1.0, 0: 2.0, 1: 3.0, 2: 4.0, 3: 8.0},
-                }
-            )
-        ],
-    )
-    def test_bar_plot_x_axis(self, plot_data):
-        df = DataFrame(plot_data)
+    def test_bar_plot_x_axis(self):
+        df = DataFrame(
+            {
+                "bars": {-1: 0.5, 0: 1.0, 1: 3.0, 2: 3.5, 3: 1.5},
+                "pct": {-1: 1.0, 0: 2.0, 1: 3.0, 2: 4.0, 3: 8.0},
+            }
+        )
         ax_bar = df["bars"].plot(kind="bar")
         df["pct"].plot(kind="line")
         actual_bar_x = [ax.get_x() + ax.get_width() / 2.0 for ax in ax_bar.patches]
         expected_x = [-1, 0, 1, 2, 3]
         assert actual_bar_x == expected_x
 
+    def test_non_numeric_bar_plt(self):
+        df = DataFrame(
+            {
+                "bars": {"a": 0.5, "b": 1.0},
+                "pct": {"a": 4.0, "b": 2.0},
+            }
+        )
+        ax_bar = df["bars"].plot(kind="bar")
+        actual_bar_x = [ax.get_x() + ax.get_width() / 2.0 for ax in ax_bar.patches]
+        expected_x = [0, 1]
+        assert actual_bar_x == expected_x
+
     @pytest.mark.slow
     def test_plot_no_warning(self, ts):
         # GH 55138