diff --git a/doc/source/v0.15.0.txt b/doc/source/v0.15.0.txt
index d15a48535f1eb..bbf665b574409 100644
--- a/doc/source/v0.15.0.txt
+++ b/doc/source/v0.15.0.txt
@@ -303,6 +303,9 @@ Enhancements
 ~~~~~~~~~~~~
 - Added support for bool, uint8, uint16 and uint32 datatypes in ``to_stata`` (:issue:`7097`, :issue:`7365`)
 
+- Added ``layout`` keyword to ``DataFrame.plot`` (:issue:`6667`)
+- Allow to pass multiple axes to ``DataFrame.plot``, ``hist`` and ``boxplot`` (:issue:`5353`, :issue:`6970`, :issue:`7069`)
+
 
 - ``PeriodIndex`` supports ``resolution`` as the same as ``DatetimeIndex`` (:issue:`7708`)
 - ``pandas.tseries.holiday`` has added support for additional holidays and ways to observe holidays (:issue:`7070`)
diff --git a/doc/source/visualization.rst b/doc/source/visualization.rst
index 40b5d7c1599c1..e8d3d147479c2 100644
--- a/doc/source/visualization.rst
+++ b/doc/source/visualization.rst
@@ -946,10 +946,41 @@ with the ``subplots`` keyword:
    @savefig frame_plot_subplots.png
    df.plot(subplots=True, figsize=(6, 6));
 
-Targeting Different Subplots
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Using Layout and Targetting Multiple Axes
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-You can pass an ``ax`` argument to :meth:`Series.plot` to plot on a particular axis:
+The layout of subplots can be specified by ``layout`` keyword. It can accept
+``(rows, columns)``. The ``layout`` keyword can be used in
+``hist`` and ``boxplot`` also. If input is invalid, ``ValueError`` will be raised.
+
+The number of axes which can be contained by rows x columns specified by ``layout`` must be
+larger than the number of required subplots. If layout can contain more axes than required,
+blank axes are not drawn.
+
+.. ipython:: python
+
+   @savefig frame_plot_subplots_layout.png
+   df.plot(subplots=True, layout=(2, 3), figsize=(6, 6));
+
+Also, you can pass multiple axes created beforehand as list-like via ``ax`` keyword.
+This allows to use more complicated layout.
+The passed axes must be the same number as the subplots being drawn.
+
+When multiple axes are passed via ``ax`` keyword, ``layout``, ``sharex`` and ``sharey`` keywords are ignored.
+These must be configured when creating axes.
+
+.. ipython:: python
+
+   fig, axes = plt.subplots(4, 4, figsize=(6, 6));
+   plt.adjust_subplots(wspace=0.5, hspace=0.5);
+   target1 = [axes[0][0], axes[1][1], axes[2][2], axes[3][3]]
+   target2 = [axes[3][0], axes[2][1], axes[1][2], axes[0][3]]
+
+   df.plot(subplots=True, ax=target1, legend=False);
+   @savefig frame_plot_subplots_multi_ax.png
+   (-df).plot(subplots=True, ax=target2, legend=False);
+
+Another option is passing an ``ax`` argument to :meth:`Series.plot` to plot on a particular axis:
 
 .. ipython:: python
    :suppress:
@@ -964,12 +995,12 @@ You can pass an ``ax`` argument to :meth:`Series.plot` to plot on a particular a
 .. ipython:: python
 
    fig, axes = plt.subplots(nrows=2, ncols=2)
-   df['A'].plot(ax=axes[0,0]); axes[0,0].set_title('A')
-   df['B'].plot(ax=axes[0,1]); axes[0,1].set_title('B')
-   df['C'].plot(ax=axes[1,0]); axes[1,0].set_title('C')
+   df['A'].plot(ax=axes[0,0]); axes[0,0].set_title('A');
+   df['B'].plot(ax=axes[0,1]); axes[0,1].set_title('B');
+   df['C'].plot(ax=axes[1,0]); axes[1,0].set_title('C');
 
    @savefig series_plot_multi.png
-   df['D'].plot(ax=axes[1,1]); axes[1,1].set_title('D')
+   df['D'].plot(ax=axes[1,1]); axes[1,1].set_title('D');
 
 .. ipython:: python
    :suppress:
diff --git a/pandas/tests/test_graphics.py b/pandas/tests/test_graphics.py
index b3a92263370e8..1560b78a2f5e0 100644
--- a/pandas/tests/test_graphics.py
+++ b/pandas/tests/test_graphics.py
@@ -670,7 +670,7 @@ def test_hist_layout_with_by(self):
         axes = _check_plot_works(df.height.hist, by=df.classroom, layout=(2, 2))
         self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
 
-        axes = _check_plot_works(df.height.hist, by=df.category, layout=(4, 2), figsize=(12, 7))
+        axes = df.height.hist(by=df.category, layout=(4, 2), figsize=(12, 7))
         self._check_axes_shape(axes, axes_num=4, layout=(4, 2), figsize=(12, 7))
 
     @slow
@@ -1071,6 +1071,7 @@ def test_subplots(self):
         for kind in ['bar', 'barh', 'line', 'area']:
             axes = df.plot(kind=kind, subplots=True, sharex=True, legend=True)
             self._check_axes_shape(axes, axes_num=3, layout=(3, 1))
+            self.assertEqual(axes.shape, (3, ))
 
             for ax, column in zip(axes, df.columns):
                 self._check_legend_labels(ax, labels=[com.pprint_thing(column)])
@@ -1133,6 +1134,77 @@ def test_subplots_timeseries(self):
                 self._check_visible(ax.get_yticklabels())
                 self._check_ticks_props(ax, xlabelsize=7, xrot=45)
 
+    def test_subplots_layout(self):
+        # GH 6667
+        df = DataFrame(np.random.rand(10, 3),
+                       index=list(string.ascii_letters[:10]))
+
+        axes = df.plot(subplots=True, layout=(2, 2))
+        self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
+        self.assertEqual(axes.shape, (2, 2))
+
+        axes = df.plot(subplots=True, layout=(1, 4))
+        self._check_axes_shape(axes, axes_num=3, layout=(1, 4))
+        self.assertEqual(axes.shape, (1, 4))
+
+        with tm.assertRaises(ValueError):
+            axes = df.plot(subplots=True, layout=(1, 1))
+
+        # single column
+        df = DataFrame(np.random.rand(10, 1),
+                       index=list(string.ascii_letters[:10]))
+        axes = df.plot(subplots=True)
+        self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
+        self.assertEqual(axes.shape, (1, ))
+
+        axes = df.plot(subplots=True, layout=(3, 3))
+        self._check_axes_shape(axes, axes_num=1, layout=(3, 3))
+        self.assertEqual(axes.shape, (3, 3))
+
+    @slow
+    def test_subplots_multiple_axes(self):
+        # GH 5353, 6970, GH 7069
+        fig, axes = self.plt.subplots(2, 3)
+        df = DataFrame(np.random.rand(10, 3),
+                       index=list(string.ascii_letters[:10]))
+
+        returned = df.plot(subplots=True, ax=axes[0])
+        self._check_axes_shape(returned, axes_num=3, layout=(1, 3))
+        self.assertEqual(returned.shape, (3, ))
+        self.assertIs(returned[0].figure, fig)
+        # draw on second row
+        returned = df.plot(subplots=True, ax=axes[1])
+        self._check_axes_shape(returned, axes_num=3, layout=(1, 3))
+        self.assertEqual(returned.shape, (3, ))
+        self.assertIs(returned[0].figure, fig)
+        self._check_axes_shape(axes, axes_num=6, layout=(2, 3))
+        tm.close()
+
+        with tm.assertRaises(ValueError):
+            fig, axes = self.plt.subplots(2, 3)
+            # pass different number of axes from required
+            df.plot(subplots=True, ax=axes)
+
+        # pass 2-dim axes and invalid layout
+        # invalid lauout should not affect to input and return value
+        # (show warning is tested in
+        # TestDataFrameGroupByPlots.test_grouped_box_multiple_axes
+        fig, axes = self.plt.subplots(2, 2)
+        df = DataFrame(np.random.rand(10, 4),
+                       index=list(string.ascii_letters[:10]))
+
+        returned = df.plot(subplots=True, ax=axes, layout=(2, 1))
+        self._check_axes_shape(returned, axes_num=4, layout=(2, 2))
+        self.assertEqual(returned.shape, (4, ))
+
+        # single column
+        fig, axes = self.plt.subplots(1, 1)
+        df = DataFrame(np.random.rand(10, 1),
+                       index=list(string.ascii_letters[:10]))
+        axes = df.plot(subplots=True, ax=[axes])
+        self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
+        self.assertEqual(axes.shape, (1, ))
+
     def test_negative_log(self):
         df = - DataFrame(rand(6, 4),
                        index=list(string.ascii_letters[:6]),
@@ -1718,7 +1790,7 @@ def test_hist_df_coord(self):
         normal_df = DataFrame({'A': np.repeat(np.array([1, 2, 3, 4, 5]),
                                               np.array([10, 9, 8, 7, 6])),
                                'B': np.repeat(np.array([1, 2, 3, 4, 5]),
-                                              np.array([8, 8, 8, 8, 8])), 
+                                              np.array([8, 8, 8, 8, 8])),
                                'C': np.repeat(np.array([1, 2, 3, 4, 5]),
                                               np.array([6, 7, 8, 9, 10]))},
                                columns=['A', 'B', 'C'])
@@ -1726,7 +1798,7 @@ def test_hist_df_coord(self):
         nan_df = DataFrame({'A': np.repeat(np.array([np.nan, 1, 2, 3, 4, 5]),
                                            np.array([3, 10, 9, 8, 7, 6])),
                             'B': np.repeat(np.array([1, np.nan, 2, 3, 4, 5]),
-                                           np.array([8, 3, 8, 8, 8, 8])), 
+                                           np.array([8, 3, 8, 8, 8, 8])),
                             'C': np.repeat(np.array([1, 2, 3, np.nan, 4, 5]),
                                            np.array([6, 7, 8, 3, 9, 10]))},
                            columns=['A', 'B', 'C'])
@@ -2712,6 +2784,41 @@ def test_grouped_box_layout(self):
             return_type='dict')
         self._check_axes_shape(self.plt.gcf().axes, axes_num=3, layout=(1, 4))
 
+    @slow
+    def test_grouped_box_multiple_axes(self):
+        # GH 6970, GH 7069
+        df = self.hist_df
+
+        # check warning to ignore sharex / sharey
+        # this check should be done in the first function which
+        # passes multiple axes to plot, hist or boxplot
+        # location should be changed if other test is added
+        # which has earlier alphabetical order
+        with tm.assert_produces_warning(UserWarning):
+            fig, axes = self.plt.subplots(2, 2)
+            df.groupby('category').boxplot(column='height', return_type='axes', ax=axes)
+            self._check_axes_shape(self.plt.gcf().axes, axes_num=4, layout=(2, 2))
+
+        fig, axes = self.plt.subplots(2, 3)
+        returned = df.boxplot(column=['height', 'weight', 'category'], by='gender',
+                              return_type='axes', ax=axes[0])
+        returned = np.array(returned.values())
+        self._check_axes_shape(returned, axes_num=3, layout=(1, 3))
+        self.assert_numpy_array_equal(returned, axes[0])
+        self.assertIs(returned[0].figure, fig)
+        # draw on second row
+        returned = df.groupby('classroom').boxplot(column=['height', 'weight', 'category'],
+                                                   return_type='axes', ax=axes[1])
+        returned = np.array(returned.values())
+        self._check_axes_shape(returned, axes_num=3, layout=(1, 3))
+        self.assert_numpy_array_equal(returned, axes[1])
+        self.assertIs(returned[0].figure, fig)
+
+        with tm.assertRaises(ValueError):
+            fig, axes = self.plt.subplots(2, 3)
+            # pass different number of axes from required
+            axes = df.groupby('classroom').boxplot(ax=axes)
+
     @slow
     def test_grouped_hist_layout(self):
 
@@ -2724,12 +2831,12 @@ def test_grouped_hist_layout(self):
         axes = _check_plot_works(df.hist, column='height', by=df.gender, layout=(2, 1))
         self._check_axes_shape(axes, axes_num=2, layout=(2, 1))
 
-        axes = _check_plot_works(df.hist, column='height', by=df.category, layout=(4, 1))
+        axes = df.hist(column='height', by=df.category, layout=(4, 1))
         self._check_axes_shape(axes, axes_num=4, layout=(4, 1))
 
-        axes = _check_plot_works(df.hist, column='height', by=df.category,
-                                 layout=(4, 2), figsize=(12, 8))
+        axes = df.hist(column='height', by=df.category, layout=(4, 2), figsize=(12, 8))
         self._check_axes_shape(axes, axes_num=4, layout=(4, 2), figsize=(12, 8))
+        tm.close()
 
         # GH 6769
         axes = _check_plot_works(df.hist, column='height', by='classroom', layout=(2, 2))
@@ -2739,13 +2846,32 @@ def test_grouped_hist_layout(self):
         axes = _check_plot_works(df.hist, by='classroom')
         self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
 
-        axes = _check_plot_works(df.hist, by='gender', layout=(3, 5))
+        axes = df.hist(by='gender', layout=(3, 5))
         self._check_axes_shape(axes, axes_num=2, layout=(3, 5))
 
-        axes = _check_plot_works(df.hist, column=['height', 'weight', 'category'])
+        axes = df.hist(column=['height', 'weight', 'category'])
         self._check_axes_shape(axes, axes_num=3, layout=(2, 2))
 
     @slow
+    def test_grouped_hist_multiple_axes(self):
+        # GH 6970, GH 7069
+        df = self.hist_df
+
+        fig, axes = self.plt.subplots(2, 3)
+        returned = df.hist(column=['height', 'weight', 'category'], ax=axes[0])
+        self._check_axes_shape(returned, axes_num=3, layout=(1, 3))
+        self.assert_numpy_array_equal(returned, axes[0])
+        self.assertIs(returned[0].figure, fig)
+        returned = df.hist(by='classroom', ax=axes[1])
+        self._check_axes_shape(returned, axes_num=3, layout=(1, 3))
+        self.assert_numpy_array_equal(returned, axes[1])
+        self.assertIs(returned[0].figure, fig)
+
+        with tm.assertRaises(ValueError):
+            fig, axes = self.plt.subplots(2, 3)
+            # pass different number of axes from required
+            axes = df.hist(column='height', ax=axes)
+    @slow
     def test_axis_share_x(self):
         df = self.hist_df
         # GH4089
diff --git a/pandas/tools/plotting.py b/pandas/tools/plotting.py
index 7d0eaea5b36d6..18fc2bead02ec 100644
--- a/pandas/tools/plotting.py
+++ b/pandas/tools/plotting.py
@@ -246,7 +246,8 @@ def scatter_matrix(frame, alpha=0.5, figsize=None, ax=None, grid=False,
 
     df = frame._get_numeric_data()
     n = df.columns.size
-    fig, axes = _subplots(nrows=n, ncols=n, figsize=figsize, ax=ax,
+    naxes = n * n
+    fig, axes = _subplots(naxes=naxes, figsize=figsize, ax=ax,
                           squeeze=False)
 
     # no gaps between subplots
@@ -752,6 +753,7 @@ class MPLPlot(object):
     data :
 
     """
+    _layout_type = 'vertical'
     _default_rot = 0
     orientation = None
 
@@ -767,7 +769,7 @@ def __init__(self, data, kind=None, by=None, subplots=False, sharex=True,
                  xticks=None, yticks=None,
                  sort_columns=False, fontsize=None,
                  secondary_y=False, colormap=None,
-                 table=False, **kwds):
+                 table=False, layout=None, **kwds):
 
         self.data = data
         self.by = by
@@ -780,6 +782,7 @@ def __init__(self, data, kind=None, by=None, subplots=False, sharex=True,
         self.sharex = sharex
         self.sharey = sharey
         self.figsize = figsize
+        self.layout = layout
 
         self.xticks = xticks
         self.yticks = yticks
@@ -932,22 +935,22 @@ def _maybe_right_yaxis(self, ax):
 
     def _setup_subplots(self):
         if self.subplots:
-            nrows, ncols = self._get_layout()
-            fig, axes = _subplots(nrows=nrows, ncols=ncols,
+            fig, axes = _subplots(naxes=self.nseries,
                                   sharex=self.sharex, sharey=self.sharey,
-                                  figsize=self.figsize, ax=self.ax)
-            if not com.is_list_like(axes):
-                axes = np.array([axes])
+                                  figsize=self.figsize, ax=self.ax,
+                                  layout=self.layout,
+                                  layout_type=self._layout_type)
         else:
             if self.ax is None:
                 fig = self.plt.figure(figsize=self.figsize)
-                ax = fig.add_subplot(111)
+                axes = fig.add_subplot(111)
             else:
                 fig = self.ax.get_figure()
                 if self.figsize is not None:
                     fig.set_size_inches(self.figsize)
-                ax = self.ax
-            axes = [ax]
+                axes = self.ax
+
+        axes = _flatten(axes)
 
         if self.logx or self.loglog:
             [a.set_xscale('log') for a in axes]
@@ -957,12 +960,18 @@ def _setup_subplots(self):
         self.fig = fig
         self.axes = axes
 
-    def _get_layout(self):
-        from pandas.core.frame import DataFrame
-        if isinstance(self.data, DataFrame):
-            return (len(self.data.columns), 1)
+    @property
+    def result(self):
+        """
+        Return result axes
+        """
+        if self.subplots:
+            if self.layout is not None and not com.is_list_like(self.ax):
+                return self.axes.reshape(*self.layout)
+            else:
+                return self.axes
         else:
-            return (1, 1)
+            return self.axes[0]
 
     def _compute_plot_data(self):
         numeric_data = self.data.convert_objects()._get_numeric_data()
@@ -1360,6 +1369,8 @@ def _get_errorbars(self, label=None, index=None, xerr=True, yerr=True):
 
 
 class ScatterPlot(MPLPlot):
+    _layout_type = 'single'
+
     def __init__(self, data, x, y, **kwargs):
         MPLPlot.__init__(self, data, **kwargs)
         self.kwds.setdefault('c', self.plt.rcParams['patch.facecolor'])
@@ -1372,8 +1383,9 @@ def __init__(self, data, x, y, **kwargs):
         self.x = x
         self.y = y
 
-    def _get_layout(self):
-        return (1, 1)
+    @property
+    def nseries(self):
+        return 1
 
     def _make_plot(self):
         x, y, data = self.x, self.y, self.data
@@ -1404,6 +1416,8 @@ def _post_plot_logic(self):
 
 
 class HexBinPlot(MPLPlot):
+    _layout_type = 'single'
+
     def __init__(self, data, x, y, C=None, **kwargs):
         MPLPlot.__init__(self, data, **kwargs)
 
@@ -1421,8 +1435,9 @@ def __init__(self, data, x, y, C=None, **kwargs):
         self.y = y
         self.C = C
 
-    def _get_layout(self):
-        return (1, 1)
+    @property
+    def nseries(self):
+        return 1
 
     def _make_plot(self):
         import matplotlib.pyplot as plt
@@ -1966,6 +1981,8 @@ def _post_plot_logic(self):
 
 class PiePlot(MPLPlot):
 
+    _layout_type = 'horizontal'
+
     def __init__(self, data, kind=None, **kwargs):
         data = data.fillna(value=0)
         if (data < 0).any().any():
@@ -1978,13 +1995,6 @@ def _args_adjust(self):
         self.logx = False
         self.loglog = False
 
-    def _get_layout(self):
-        from pandas import DataFrame
-        if isinstance(self.data, DataFrame):
-            return (1, len(self.data.columns))
-        else:
-            return (1, 1)
-
     def _validate_color_args(self):
         pass
 
@@ -2044,7 +2054,7 @@ def plot_frame(frame=None, x=None, y=None, subplots=False, sharex=True,
                legend=True, rot=None, ax=None, style=None, title=None,
                xlim=None, ylim=None, logx=False, logy=False, xticks=None,
                yticks=None, kind='line', sort_columns=False, fontsize=None,
-               secondary_y=False, **kwds):
+               secondary_y=False, layout=None, **kwds):
 
     """
     Make line, bar, or scatter plots of DataFrame series with the index on the x-axis
@@ -2116,6 +2126,8 @@ def plot_frame(frame=None, x=None, y=None, subplots=False, sharex=True,
     position : float
         Specify relative alignments for bar plot layout.
         From 0 (left/bottom-end) to 1 (right/top-end). Default is 0.5 (center)
+    layout : tuple (optional)
+        (rows, columns) for the layout of the plot
     table : boolean, Series or DataFrame, default False
         If True, draw a table using the data in the DataFrame and the data will
         be transposed to meet matplotlib's default layout.
@@ -2153,7 +2165,7 @@ def plot_frame(frame=None, x=None, y=None, subplots=False, sharex=True,
                          xlim=xlim, ylim=ylim, title=title, grid=grid,
                          figsize=figsize, logx=logx, logy=logy,
                          sort_columns=sort_columns, secondary_y=secondary_y,
-                         **kwds)
+                         layout=layout, **kwds)
     elif kind in _series_kinds:
         if y is None and subplots is False:
             msg = "{0} requires either y column or 'subplots=True'"
@@ -2169,9 +2181,8 @@ def plot_frame(frame=None, x=None, y=None, subplots=False, sharex=True,
                          fontsize=fontsize, use_index=use_index, sharex=sharex,
                          sharey=sharey, xticks=xticks, yticks=yticks,
                          xlim=xlim, ylim=ylim, title=title, grid=grid,
-                         figsize=figsize,
-                         sort_columns=sort_columns,
-                         **kwds)
+                         figsize=figsize, layout=layout,
+                         sort_columns=sort_columns, **kwds)
     else:
         if x is not None:
             if com.is_integer(x) and not frame.columns.holds_integer():
@@ -2209,14 +2220,11 @@ def plot_frame(frame=None, x=None, y=None, subplots=False, sharex=True,
                              xticks=xticks, yticks=yticks, xlim=xlim, ylim=ylim,
                              title=title, grid=grid, figsize=figsize, logx=logx,
                              logy=logy, sort_columns=sort_columns,
-                             secondary_y=secondary_y, **kwds)
+                             secondary_y=secondary_y, layout=layout, **kwds)
 
     plot_obj.generate()
     plot_obj.draw()
-    if subplots:
-        return plot_obj.axes
-    else:
-        return plot_obj.axes[0]
+    return plot_obj.result
 
 
 def plot_series(series, label=None, kind='line', use_index=True, rot=None,
@@ -2311,7 +2319,7 @@ def plot_series(series, label=None, kind='line', use_index=True, rot=None,
     plot_obj.draw()
 
     # plot_obj.ax is None if we created the first figure
-    return plot_obj.axes[0]
+    return plot_obj.result
 
 
 _shared_docs['boxplot'] = """
@@ -2551,12 +2559,13 @@ def hist_frame(data, column=None, by=None, grid=True, xlabelsize=None,
     data = data._get_numeric_data()
     naxes = len(data.columns)
 
-    nrows, ncols = _get_layout(naxes, layout=layout)
-    fig, axes = _subplots(nrows=nrows, ncols=ncols, naxes=naxes, ax=ax, squeeze=False,
-                          sharex=sharex, sharey=sharey, figsize=figsize)
+    fig, axes = _subplots(naxes=naxes, ax=ax, squeeze=False,
+                          sharex=sharex, sharey=sharey, figsize=figsize,
+                          layout=layout)
+    _axes = _flatten(axes)
 
     for i, col in enumerate(com._try_sort(data.columns)):
-        ax = axes[i // ncols, i % ncols]
+        ax = _axes[i]
         ax.hist(data[col].dropna().values, bins=bins, **kwds)
         ax.set_title(col)
         ax.grid(grid)
@@ -2672,7 +2681,7 @@ def plot_group(group, ax):
     xrot = xrot or rot
 
     fig, axes = _grouped_plot(plot_group, data, column=column,
-                              by=by, sharex=sharex, sharey=sharey,
+                              by=by, sharex=sharex, sharey=sharey, ax=ax,
                               figsize=figsize, layout=layout, rot=rot)
 
     _set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
@@ -2730,9 +2739,9 @@ def boxplot_frame_groupby(grouped, subplots=True, column=None, fontsize=None,
     """
     if subplots is True:
         naxes = len(grouped)
-        nrows, ncols = _get_layout(naxes, layout=layout)
-        fig, axes = _subplots(nrows=nrows, ncols=ncols, naxes=naxes, squeeze=False,
-                              ax=ax, sharex=False, sharey=True, figsize=figsize)
+        fig, axes = _subplots(naxes=naxes, squeeze=False,
+                              ax=ax, sharex=False, sharey=True, figsize=figsize,
+                              layout=layout)
         axes = _flatten(axes)
 
         ret = compat.OrderedDict()
@@ -2773,14 +2782,14 @@ def _grouped_plot(plotf, data, column=None, by=None, numeric_only=True,
         grouped = grouped[column]
 
     naxes = len(grouped)
-    nrows, ncols = _get_layout(naxes, layout=layout)
-    fig, axes = _subplots(nrows=nrows, ncols=ncols, naxes=naxes,
-                          figsize=figsize, sharex=sharex, sharey=sharey, ax=ax)
+    fig, axes = _subplots(naxes=naxes, figsize=figsize,
+                          sharex=sharex, sharey=sharey, ax=ax,
+                          layout=layout)
 
-    ravel_axes = _flatten(axes)
+    _axes = _flatten(axes)
 
     for i, (key, group) in enumerate(grouped):
-        ax = ravel_axes[i]
+        ax = _axes[i]
         if numeric_only and isinstance(group, DataFrame):
             group = group._get_numeric_data()
         plotf(group, ax, **kwargs)
@@ -2799,16 +2808,14 @@ def _grouped_plot_by_column(plotf, data, columns=None, by=None,
             by = [by]
         columns = data._get_numeric_data().columns - by
     naxes = len(columns)
-    nrows, ncols = _get_layout(naxes, layout=layout)
-    fig, axes = _subplots(nrows=nrows, ncols=ncols, naxes=naxes,
-                          sharex=True, sharey=True,
-                          figsize=figsize, ax=ax)
+    fig, axes = _subplots(naxes=naxes, sharex=True, sharey=True,
+                          figsize=figsize, ax=ax, layout=layout)
 
-    ravel_axes = _flatten(axes)
+    _axes = _flatten(axes)
 
     result = compat.OrderedDict()
     for i, col in enumerate(columns):
-        ax = ravel_axes[i]
+        ax = _axes[i]
         gp_col = grouped[col]
         keys, values = zip(*gp_col)
         re_plotf = plotf(keys, values, ax, **kwargs)
@@ -2869,7 +2876,7 @@ def table(ax, data, rowLabels=None, colLabels=None,
     return table
 
 
-def _get_layout(nplots, layout=None):
+def _get_layout(nplots, layout=None, layout_type='box'):
     if layout is not None:
         if not isinstance(layout, (tuple, list)) or len(layout) != 2:
             raise ValueError('Layout must be a tuple of (rows, columns)')
@@ -2881,27 +2888,31 @@ def _get_layout(nplots, layout=None):
 
         return layout
 
-    if nplots == 1:
+    if layout_type == 'single':
         return (1, 1)
-    elif nplots == 2:
-        return (1, 2)
-    elif nplots < 4:
-        return (2, 2)
+    elif layout_type == 'horizontal':
+        return (1, nplots)
+    elif layout_type == 'vertical':
+        return (nplots, 1)
 
-    k = 1
-    while k ** 2 < nplots:
-        k += 1
-
-    if (k - 1) * k >= nplots:
-        return k, (k - 1)
-    else:
-        return k, k
+    layouts = {1: (1, 1), 2: (1, 2), 3: (2, 2), 4: (2, 2)}
+    try:
+        return layouts[nplots]
+    except KeyError:
+        k = 1
+        while k ** 2 < nplots:
+            k += 1
+
+        if (k - 1) * k >= nplots:
+            return k, (k - 1)
+        else:
+            return k, k
 
-# copied from matplotlib/pyplot.py for compatibility with matplotlib < 1.0
+# copied from matplotlib/pyplot.py and modified for pandas.plotting
 
 
-def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=True,
-              subplot_kw=None, ax=None, **fig_kw):
+def _subplots(naxes=None, sharex=False, sharey=False, squeeze=True,
+              subplot_kw=None, ax=None, layout=None, layout_type='box', **fig_kw):
     """Create a figure with a set of subplots already made.
 
     This utility wrapper makes it convenient to create common layouts of
@@ -2909,12 +2920,6 @@ def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=
 
     Keyword arguments:
 
-    nrows : int
-      Number of rows of the subplot grid.  Defaults to 1.
-
-    ncols : int
-      Number of columns of the subplot grid.  Defaults to 1.
-
     naxes : int
       Number of required axes. Exceeded axes are set invisible. Default is nrows * ncols.
 
@@ -2942,11 +2947,17 @@ def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=
 
     ax : Matplotlib axis object, optional
 
+    layout : tuple
+      Number of rows and columns of the subplot grid.
+      If not specified, calculated from naxes and layout_type
+
+    layout_type : {'box', 'horziontal', 'vertical'}, default 'box'
+      Specify how to layout the subplot grid.
+
     fig_kw : Other keyword arguments to be passed to the figure() call.
         Note that all keywords not recognized above will be
         automatically included here.
 
-
     Returns:
 
     fig, ax : tuple
@@ -2975,23 +2986,27 @@ def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=
     plt.subplots(2, 2, subplot_kw=dict(polar=True))
     """
     import matplotlib.pyplot as plt
-    from pandas.core.frame import DataFrame
 
     if subplot_kw is None:
         subplot_kw = {}
 
-    # Create empty object array to hold all axes.  It's easiest to make it 1-d
-    # so we can just append subplots upon creation, and then
-    nplots = nrows * ncols
-
-    if naxes is None:
-        naxes = nrows * ncols
-    elif nplots < naxes:
-        raise ValueError("naxes {0} is larger than layour size defined by nrows * ncols".format(naxes))
-
     if ax is None:
         fig = plt.figure(**fig_kw)
     else:
+        if com.is_list_like(ax):
+            ax = _flatten(ax)
+            if layout is not None:
+                warnings.warn("When passing multiple axes, layout keyword is ignored", UserWarning)
+            if sharex or sharey:
+                warnings.warn("When passing multiple axes, sharex and sharey are ignored."
+                              "These settings must be specified when creating axes", UserWarning)
+            if len(ax) == naxes:
+                fig = ax[0].get_figure()
+                return fig, ax
+            else:
+                raise ValueError("The number of passed axes must be {0}, the same as "
+                                 "the output plot".format(naxes))
+
         fig = ax.get_figure()
          # if ax is passed and a number of subplots is 1, return ax as it is
         if naxes == 1:
@@ -3004,6 +3019,11 @@ def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=
                           "is being cleared", UserWarning)
             fig.clear()
 
+    nrows, ncols = _get_layout(naxes, layout=layout, layout_type=layout_type)
+    nplots = nrows * ncols
+
+    # Create empty object array to hold all axes.  It's easiest to make it 1-d
+    # so we can just append subplots upon creation, and then
     axarr = np.empty(nplots, dtype=object)
 
     # Create first subplot separately, so we can share it if requested
@@ -3074,10 +3094,10 @@ def _subplots(nrows=1, ncols=1, naxes=None, sharex=False, sharey=False, squeeze=
 
 def _flatten(axes):
     if not com.is_list_like(axes):
-        axes = [axes]
+        return np.array([axes])
     elif isinstance(axes, (np.ndarray, Index)):
-        axes = axes.ravel()
-    return axes
+        return axes.ravel()
+    return np.array(axes)
 
 
 def _get_all_lines(ax):