fixing style issues

Author: javadnoorb

pandas/plotting/_core.py

@@ -870,7 +870,12 @@ def _make_plot(self):
         scatter = ax.scatter(data[x].values, data[y].values, c=c_values,
                              label=label, cmap=cmap, **self.kwds)
         if cb:
+            # The following attribute determines which axes belong to
+            # colorbars. When sharex = True, this allows `_handle_shared_axes`
+            # to skip them. Otherwise colobars will cause x-axis label and
+            # tick labels to disappear.
             ax._pandas_colorbar_axes = True
+
             img = ax.collections[0]
             kws = dict(ax=ax)
             if self.mpl_ge_1_3_1():
@@ -917,7 +922,12 @@ def _make_plot(self):
         ax.hexbin(data[x].values, data[y].values, C=c_values, cmap=cmap,
                   **self.kwds)
         if cb:
+            # The following attribute determines which axes belong to
+            # colorbars. When sharex = True, this allows `_handle_shared_axes`
+            # to skip them. Otherwise colobars will cause x-axis label and
+            # tick labels to disappear.
             ax._pandas_colorbar_axes = True
+
             img = ax.collections[0]
             self.fig.colorbar(img, ax=ax)
 

pandas/plotting/_tools.py

@@ -311,8 +311,8 @@ def _handle_shared_axes(axarr, nplots, naxes, nrows, ncols, sharex, sharey):
                     # only the last row of subplots should get x labels -> all
                     # other off layout handles the case that the subplot is
                     # the last in the column, because below is no subplot/gap.
-                    if not layout[ax.rowNum + 1, ax.colNum] or \
-                            getattr(ax, '_pandas_colorbar_axes', False):
+                    if (not layout[ax.rowNum + 1, ax.colNum] or
+                            getattr(ax, '_pandas_colorbar_axes', False)):
                         continue
                     if sharex or len(ax.get_shared_x_axes()
                                      .get_siblings(ax)) > 1:

pandas/tests/plotting/test_frame.py

@@ -1033,39 +1033,39 @@ def test_plot_scatter(self):
     @pytest.mark.slow
     def test_if_scatterplot_colorbar_affects_xaxis_visibility(self):
         random_array = np.random.random((1000, 3))
-        df = pd.DataFrame(random_array,columns=['A label', 'B label', 'C label'])
+        df = pd.DataFrame(random_array,
+                          columns=['A label', 'B label', 'C label'])
 
         ax1 = df.plot.scatter(x='A label', y='B label')
         ax2 = df.plot.scatter(x='A label', y='B label', c='C label')
 
-        assert all([vis[0].get_visible() == vis[1].get_visible() for vis in
-                    zip(ax1.xaxis.get_minorticklabels(),
-                        ax2.xaxis.get_minorticklabels())]), \
-            'minor x-axis tick labels visibility ' \
-            'changes when colorbar included'
-        assert all([vis[0].get_visible() == vis[1].get_visible() for vis in
-                    zip(ax1.xaxis.get_majorticklabels(),
-                        ax2.xaxis.get_majorticklabels())]), \
-            'major x-axis tick labels visibility ' \
-            'changes when colorbar included'
-        assert ax1.xaxis.get_label().get_visible() == \
-            ax2.xaxis.get_label().get_visible(), \
-            'x-axis label visibility changes when colorbar included'
+        vis1 = [vis.get_visible() for vis in
+                ax1.xaxis.get_minorticklabels()]
+        vis2 = [vis.get_visible() for vis in
+                ax2.xaxis.get_minorticklabels()]
+        assert vis1 == vis2
+
+        vis1 = [vis.get_visible() for vis in
+                ax1.xaxis.get_majorticklabels()]
+        vis2 = [vis.get_visible() for vis in
+                ax2.xaxis.get_majorticklabels()]
+        assert vis1 == vis2
+
+        assert (ax1.xaxis.get_label().get_visible() ==
+                ax2.xaxis.get_label().get_visible())
 
     @pytest.mark.slow
     def test_if_hexbin_xaxis_label_is_visible(self):
         random_array = np.random.random((1000, 3))
-        df = pd.DataFrame(random_array,columns=['A label', 'B label', 'C label'])
+        df = pd.DataFrame(random_array,
+                          columns=['A label', 'B label', 'C label'])
 
         ax = df.plot.hexbin('A label', 'B label', gridsize=12)
         assert all([vis.get_visible() for vis in
-                    ax.xaxis.get_minorticklabels()]), \
-            'minor x-axis tick labels are not visible'
+                    ax.xaxis.get_minorticklabels()])
         assert all([vis.get_visible() for vis in
-                    ax.xaxis.get_majorticklabels()]), \
-            'major x-axis tick labels are not visible'
-        assert ax.xaxis.get_label().get_visible(), \
-            'x-axis label is not visible'
+                    ax.xaxis.get_majorticklabels()])
+        assert ax.xaxis.get_label().get_visible()
 
     @pytest.mark.slow
     def test_plot_scatter_with_categorical_data(self):