TST: Modify tests/plotting/test_frame.test_bar_categorical

Ticklocs are now float also for categorical bar data (as they are
position on the axis). The test is changed to compare to a array of
np.float.

Author: nrebena

pandas/plotting/_matplotlib/core.py

@@ -1357,11 +1357,11 @@ def _make_plot(self):
         for i, (label, y) in enumerate(self._iter_data(fillna=0)):
             ax = self._get_ax(i)
 
-            if self.orientation == 'vertical':
+            if self.orientation == "vertical":
                 ax.xaxis.update_units(self.ax_index)
                 self.tick_pos = ax.convert_xunits(self.ax_index)
                 self.ax_pos = self.tick_pos - self.tickoffset
-            elif self.orientation == 'horizontal':
+            elif self.orientation == "horizontal":
                 ax.yaxis.update_units(self.ax_index)
                 self.tick_pos = ax.convert_yunits(self.ax_index)
                 self.ax_pos = self.tick_pos - self.tickoffset

pandas/tests/plotting/test_frame.py

@@ -1130,14 +1130,18 @@ def test_bar_categorical(self):
         for df in [df1, df2]:
             ax = df.plot.bar()
             ticks = ax.xaxis.get_ticklocs()
-            tm.assert_numpy_array_equal(ticks, np.array([0, 1, 2, 3, 4, 5]))
+            tm.assert_numpy_array_equal(
+                ticks, np.array([0, 1, 2, 3, 4, 5], dtype=np.float)
+            )
             assert ax.get_xlim() == (-0.5, 5.5)
             # check left-edge of bars
             assert ax.patches[0].get_x() == -0.25
             assert ax.patches[-1].get_x() == 5.15
 
             ax = df.plot.bar(stacked=True)
-            tm.assert_numpy_array_equal(ticks, np.array([0, 1, 2, 3, 4, 5]))
+            tm.assert_numpy_array_equal(
+                ticks, np.array([0, 1, 2, 3, 4, 5], dtype=np.float)
+            )
             assert ax.get_xlim() == (-0.5, 5.5)
             assert ax.patches[0].get_x() == -0.25
             assert ax.patches[-1].get_x() == 4.75
@@ -3251,30 +3255,27 @@ def test_plot_no_numeric_data(self):
             df.plot()
 
     @pytest.mark.slow
-    @pytest.mark.parametrize('method', ['bar', 'barh'])
+    @pytest.mark.parametrize("method", ["bar", "barh"])
     def test_bar_ticklabel_consistence(self, method):
         # Draw two consecutiv bar plot with consistent ticklabels
         # GH: 26186
         def get_main_axis(ax):
-            if method == 'barh':
+            if method == "barh":
                 return ax.yaxis
-            elif method == 'bar':
+            elif method == "bar":
                 return ax.xaxis
+
         data = {"A": 0, "B": 3, "C": -4}
         df = pd.DataFrame.from_dict(data, orient="index", columns=["Value"])
         ax = getattr(df.plot, method)()
         ax.get_figure().canvas.draw()
-        xticklabels = [t.get_text()
-                       for t in get_main_axis(ax).get_ticklabels()]
-        label_positions_1 = dict(zip(xticklabels,
-                                     get_main_axis(ax).get_ticklocs()))
-        df = df.sort_values("Value") * - 2
+        xticklabels = [t.get_text() for t in get_main_axis(ax).get_ticklabels()]
+        label_positions_1 = dict(zip(xticklabels, get_main_axis(ax).get_ticklocs()))
+        df = df.sort_values("Value") * -2
         ax = getattr(df.plot, method)(ax=ax, color="red")
         ax.get_figure().canvas.draw()
-        xticklabels = [t.get_text()
-                       for t in get_main_axis(ax).get_ticklabels()]
-        label_positions_2 = dict(zip(xticklabels,
-                                     get_main_axis(ax).get_ticklocs()))
+        xticklabels = [t.get_text() for t in get_main_axis(ax).get_ticklabels()]
+        label_positions_2 = dict(zip(xticklabels, get_main_axis(ax).get_ticklocs()))
         assert label_positions_1 == label_positions_2
 
     def test_bar_numeric(self):