BUG: Fix plots showing multiple sets of axis labels if index is a timeseries.

doc/source/whatsnew/v0.15.2.txt

@@ -222,3 +222,5 @@ Bug Fixes
 
 
 - Fixed ValueError raised by cummin/cummax when datetime64 Series contains NaT. (:issue:`8965`)
+- Bug in plotting if sharex was enabled and index was a timeseries, would show labels on multiple axes (:issue:`3964`).
+

pandas/tests/test_graphics.py

@@ -1329,6 +1329,32 @@ def test_subplots_multiple_axes(self):
         self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
         self.assertEqual(axes.shape, (1, ))
 
+    def test_subplots_ts_share_axes(self):
+        # GH 3964
+        fig, axes = self.plt.subplots(3, 3, sharex=True, sharey=True)
+        self.plt.subplots_adjust(left=0.05, right=0.95, hspace=0.3, wspace=0.3)
+        df = DataFrame(np.random.randn(10, 9), index=date_range(start='2014-07-01', freq='M', periods=10))
+        for i, ax in enumerate(axes.ravel()):
+            df[i].plot(ax=ax, fontsize=5)
+
+        #Rows other than bottom should not be visible
+        for ax in axes[0:-1].ravel():
+            self._check_visible(ax.get_xticklabels(), visible=False)
+
+        #Bottom row should be visible
+        for ax in axes[-1].ravel():
+            self._check_visible(ax.get_xticklabels(), visible=True)
+
+        #First column should be visible
+        for ax in axes[[0, 1, 2], [0]].ravel():
+            self._check_visible(ax.get_yticklabels(), visible=True)
+
+        #Other columns should not be visible
+        for ax in axes[[0, 1, 2], [1]].ravel():
+            self._check_visible(ax.get_yticklabels(), visible=False)
+        for ax in axes[[0, 1, 2], [2]].ravel():
+            self._check_visible(ax.get_yticklabels(), visible=False)
+
     def test_negative_log(self):
         df = - DataFrame(rand(6, 4),
                        index=list(string.ascii_letters[:6]),

pandas/tools/plotting.py

@@ -1022,7 +1022,10 @@ def _post_plot_logic(self):
     def _adorn_subplots(self):
         to_adorn = self.axes
 
-        # todo: sharex, sharey handling?
+        if len(self.axes) > 0:
+            all_axes = self._get_axes()
+            nrows, ncols = self._get_axes_layout()
+            _handle_shared_axes(all_axes, len(all_axes), len(all_axes), nrows, ncols, self.sharex, self.sharey)
 
         for ax in to_adorn:
             if self.yticks is not None:
@@ -1375,6 +1378,19 @@ def _get_errorbars(self, label=None, index=None, xerr=True, yerr=True):
                     errors[kw] = err
         return errors
 
+    def _get_axes(self):
+        return self.axes[0].get_figure().get_axes()
+
+    def _get_axes_layout(self):
+        axes = self._get_axes()
+        x_set = set()
+        y_set = set()
+        for ax in axes:
+            # check axes coordinates to estimate layout
+            points = ax.get_position().get_points()
+            x_set.add(points[0][0])
+            y_set.add(points[0][1])
+        return (len(y_set), len(x_set))
 
 class ScatterPlot(MPLPlot):
     _layout_type = 'single'
@@ -3231,6 +3247,28 @@ def _subplots(naxes=None, sharex=False, sharey=False, squeeze=True,
         ax = fig.add_subplot(nrows, ncols, i + 1, **kwds)
         axarr[i] = ax
 
+    _handle_shared_axes(axarr, nplots, naxes, nrows, ncols, sharex, sharey)
+
+    if naxes != nplots:
+        for ax in axarr[naxes:]:
+            ax.set_visible(False)
+
+    if squeeze:
+        # Reshape the array to have the final desired dimension (nrow,ncol),
+        # though discarding unneeded dimensions that equal 1.  If we only have
+        # one subplot, just return it instead of a 1-element array.
+        if nplots == 1:
+            axes = axarr[0]
+        else:
+            axes = axarr.reshape(nrows, ncols).squeeze()
+    else:
+        # returned axis array will be always 2-d, even if nrows=ncols=1
+        axes = axarr.reshape(nrows, ncols)
+
+    return fig, axes
+
+
+def _handle_shared_axes(axarr, nplots, naxes, nrows, ncols, sharex, sharey):
     if nplots > 1:
 
         if sharex and nrows > 1:
@@ -3241,8 +3279,11 @@ def _subplots(naxes=None, sharex=False, sharey=False, squeeze=True,
                     # set_visible will not be effective if
                     # minor axis has NullLocator and NullFormattor (default)
                     import matplotlib.ticker as ticker
-                    ax.xaxis.set_minor_locator(ticker.AutoLocator())
-                    ax.xaxis.set_minor_formatter(ticker.FormatStrFormatter(''))
+
+                    if isinstance(ax.xaxis.get_minor_locator(), ticker.NullLocator):
+                        ax.xaxis.set_minor_locator(ticker.AutoLocator())
+                    if isinstance(ax.xaxis.get_minor_formatter(), ticker.NullFormatter):
+                        ax.xaxis.set_minor_formatter(ticker.FormatStrFormatter(''))
                     for label in ax.get_xticklabels(minor=True):
                         label.set_visible(False)
                 except Exception:   # pragma no cover
@@ -3255,32 +3296,16 @@ def _subplots(naxes=None, sharex=False, sharey=False, squeeze=True,
                         label.set_visible(False)
                     try:
                         import matplotlib.ticker as ticker
-                        ax.yaxis.set_minor_locator(ticker.AutoLocator())
-                        ax.yaxis.set_minor_formatter(ticker.FormatStrFormatter(''))
+                        if isinstance(ax.yaxis.get_minor_locator(), ticker.NullLocator):
+                            ax.yaxis.set_minor_locator(ticker.AutoLocator())
+                        if isinstance(ax.yaxis.get_minor_formatter(), ticker.NullFormatter):
+                            ax.yaxis.set_minor_formatter(ticker.FormatStrFormatter(''))
                         for label in ax.get_yticklabels(minor=True):
                             label.set_visible(False)
                     except Exception:   # pragma no cover
                         pass
                     ax.yaxis.get_label().set_visible(False)
 
-    if naxes != nplots:
-        for ax in axarr[naxes:]:
-            ax.set_visible(False)
-
-    if squeeze:
-        # Reshape the array to have the final desired dimension (nrow,ncol),
-        # though discarding unneeded dimensions that equal 1.  If we only have
-        # one subplot, just return it instead of a 1-element array.
-        if nplots == 1:
-            axes = axarr[0]
-        else:
-            axes = axarr.reshape(nrows, ncols).squeeze()
-    else:
-        # returned axis array will be always 2-d, even if nrows=ncols=1
-        axes = axarr.reshape(nrows, ncols)
-
-    return fig, axes
-
 
 def _flatten(axes):
     if not com.is_list_like(axes):