COMPAT: Support for MPL 1.5

ci/install_conda.sh

@@ -72,6 +72,7 @@ bash miniconda.sh -b -p $HOME/miniconda || exit 1
 
 conda config --set always_yes yes --set changeps1 no || exit 1
 conda update -q conda || exit 1
+conda config --add channels conda-forge || exit 1
 conda config --add channels http://conda.binstar.org/pandas || exit 1
 conda config --set ssl_verify false || exit 1
 

ci/requirements-3.4.run

@@ -11,7 +11,6 @@ beautiful-soup
 scipy
 numexpr
 pytables
-matplotlib=1.3.1
 lxml
 sqlalchemy
 bottleneck

doc/source/whatsnew/v0.17.0.txt

@@ -50,6 +50,7 @@ Highlights include:
 - Documentation comparing SAS to *pandas*, see :ref:`here <compare_with_sas>`
 - Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see :ref:`here <whatsnew_0170.prior_deprecations>`
 - Compatibility with Python 3.5 (:issue:`11097`)
+- Compatibility with matplotlib 1.5.0 (:issue:`11111`)
 
 Check the :ref:`API Changes <whatsnew_0170.api>` and :ref:`deprecations <whatsnew_0170.deprecations>` before updating.
 

pandas/tests/test_graphics_others.py

@@ -161,22 +161,22 @@ def test_plot_fails_when_ax_differs_from_figure(self):
     @slow
     def test_autocorrelation_plot(self):
         from pandas.tools.plotting import autocorrelation_plot
-        _check_plot_works(autocorrelation_plot, self.ts)
-        _check_plot_works(autocorrelation_plot, self.ts.values)
+        _check_plot_works(autocorrelation_plot, series=self.ts)
+        _check_plot_works(autocorrelation_plot, series=self.ts.values)
 
         ax = autocorrelation_plot(self.ts, label='Test')
         self._check_legend_labels(ax, labels=['Test'])
 
     @slow
     def test_lag_plot(self):
         from pandas.tools.plotting import lag_plot
-        _check_plot_works(lag_plot, self.ts)
-        _check_plot_works(lag_plot, self.ts, lag=5)
+        _check_plot_works(lag_plot, series=self.ts)
+        _check_plot_works(lag_plot, series=self.ts, lag=5)
 
     @slow
     def test_bootstrap_plot(self):
         from pandas.tools.plotting import bootstrap_plot
-        _check_plot_works(bootstrap_plot, self.ts, size=10)
+        _check_plot_works(bootstrap_plot, series=self.ts, size=10)
 
 
 @tm.mplskip
@@ -210,7 +210,7 @@ def test_boxplot_legacy(self):
         _check_plot_works(df.boxplot, column='one', by=['indic', 'indic2'])
         _check_plot_works(df.boxplot, by='indic')
         _check_plot_works(df.boxplot, by=['indic', 'indic2'])
-        _check_plot_works(plotting.boxplot, df['one'], return_type='dict')
+        _check_plot_works(plotting.boxplot, data=df['one'], return_type='dict')
         _check_plot_works(df.boxplot, notch=1, return_type='dict')
         _check_plot_works(df.boxplot, by='indic', notch=1)
 
@@ -304,6 +304,7 @@ def test_boxplot_empty_column(self):
 
     @slow
     def test_hist_df_legacy(self):
+        from matplotlib.patches import Rectangle
         _check_plot_works(self.hist_df.hist)
 
         # make sure layout is handled
@@ -347,7 +348,8 @@ def test_hist_df_legacy(self):
         # make sure kwargs to hist are handled
         ax = ser.hist(normed=True, cumulative=True, bins=4)
         # height of last bin (index 5) must be 1.0
-        self.assertAlmostEqual(ax.get_children()[5].get_height(), 1.0)
+        rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
+        self.assertAlmostEqual(rects[-1].get_height(), 1.0)
 
         tm.close()
         ax = ser.hist(log=True)
@@ -413,9 +415,9 @@ def scat(**kwds):
         def scat2(x, y, by=None, ax=None, figsize=None):
             return plotting.scatter_plot(df, x, y, by, ax, figsize=None)
 
-        _check_plot_works(scat2, 0, 1)
+        _check_plot_works(scat2, x=0, y=1)
         grouper = Series(np.repeat([1, 2, 3, 4, 5], 20), df.index)
-        _check_plot_works(scat2, 0, 1, by=grouper)
+        _check_plot_works(scat2, x=0, y=1, by=grouper)
 
     def test_scatter_matrix_axis(self):
         tm._skip_if_no_scipy()
@@ -424,15 +426,17 @@ def test_scatter_matrix_axis(self):
         with tm.RNGContext(42):
             df = DataFrame(randn(100, 3))
 
-        axes = _check_plot_works(scatter_matrix, df, range_padding=.1)
+        axes = _check_plot_works(scatter_matrix, filterwarnings='always', frame=df,
+                                 range_padding=.1)
         axes0_labels = axes[0][0].yaxis.get_majorticklabels()
         # GH 5662
         expected = ['-2', '-1', '0', '1', '2']
         self._check_text_labels(axes0_labels, expected)
         self._check_ticks_props(axes, xlabelsize=8, xrot=90, ylabelsize=8, yrot=0)
 
         df[0] = ((df[0] - 2) / 3)
-        axes = _check_plot_works(scatter_matrix, df, range_padding=.1)
+        axes = _check_plot_works(scatter_matrix, filterwarnings='always', frame=df,
+                                 range_padding=.1)
         axes0_labels = axes[0][0].yaxis.get_majorticklabels()
         expected = ['-1.2', '-1.0', '-0.8', '-0.6', '-0.4', '-0.2', '0.0']
         self._check_text_labels(axes0_labels, expected)
@@ -445,17 +449,17 @@ def test_andrews_curves(self):
 
         df = self.iris
 
-        _check_plot_works(andrews_curves, df, 'Name')
+        _check_plot_works(andrews_curves, frame=df, class_column='Name')
 
         rgba = ('#556270', '#4ECDC4', '#C7F464')
-        ax = _check_plot_works(andrews_curves, df, 'Name', color=rgba)
+        ax = _check_plot_works(andrews_curves, frame=df, class_column='Name', color=rgba)
         self._check_colors(ax.get_lines()[:10], linecolors=rgba, mapping=df['Name'][:10])
 
         cnames = ['dodgerblue', 'aquamarine', 'seagreen']
-        ax = _check_plot_works(andrews_curves, df, 'Name', color=cnames)
+        ax = _check_plot_works(andrews_curves, frame=df, class_column='Name', color=cnames)
         self._check_colors(ax.get_lines()[:10], linecolors=cnames, mapping=df['Name'][:10])
 
-        ax = _check_plot_works(andrews_curves, df, 'Name', colormap=cm.jet)
+        ax = _check_plot_works(andrews_curves, frame=df, class_column='Name', colormap=cm.jet)
         cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
         self._check_colors(ax.get_lines()[:10], linecolors=cmaps, mapping=df['Name'][:10])
 
@@ -478,23 +482,23 @@ def test_parallel_coordinates(self):
 
         df = self.iris
 
-        ax = _check_plot_works(parallel_coordinates, df, 'Name')
+        ax = _check_plot_works(parallel_coordinates, frame=df, class_column='Name')
         nlines = len(ax.get_lines())
         nxticks = len(ax.xaxis.get_ticklabels())
 
         rgba = ('#556270', '#4ECDC4', '#C7F464')
-        ax = _check_plot_works(parallel_coordinates, df, 'Name', color=rgba)
+        ax = _check_plot_works(parallel_coordinates, frame=df, class_column='Name', color=rgba)
         self._check_colors(ax.get_lines()[:10], linecolors=rgba, mapping=df['Name'][:10])
 
         cnames = ['dodgerblue', 'aquamarine', 'seagreen']
-        ax = _check_plot_works(parallel_coordinates, df, 'Name', color=cnames)
+        ax = _check_plot_works(parallel_coordinates, frame=df, class_column='Name', color=cnames)
         self._check_colors(ax.get_lines()[:10], linecolors=cnames, mapping=df['Name'][:10])
 
-        ax = _check_plot_works(parallel_coordinates, df, 'Name', colormap=cm.jet)
+        ax = _check_plot_works(parallel_coordinates, frame=df, class_column='Name', colormap=cm.jet)
         cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
         self._check_colors(ax.get_lines()[:10], linecolors=cmaps, mapping=df['Name'][:10])
 
-        ax = _check_plot_works(parallel_coordinates, df, 'Name', axvlines=False)
+        ax = _check_plot_works(parallel_coordinates, frame=df, class_column='Name', axvlines=False)
         assert len(ax.get_lines()) == (nlines - nxticks)
 
         colors = ['b', 'g', 'r']
@@ -517,20 +521,20 @@ def test_radviz(self):
         from matplotlib import cm
 
         df = self.iris
-        _check_plot_works(radviz, df, 'Name')
+        _check_plot_works(radviz, frame=df, class_column='Name')
 
         rgba = ('#556270', '#4ECDC4', '#C7F464')
-        ax = _check_plot_works(radviz, df, 'Name', color=rgba)
+        ax = _check_plot_works(radviz, frame=df, class_column='Name', color=rgba)
         # skip Circle drawn as ticks
         patches = [p for p in ax.patches[:20] if p.get_label() != '']
         self._check_colors(patches[:10], facecolors=rgba, mapping=df['Name'][:10])
 
         cnames = ['dodgerblue', 'aquamarine', 'seagreen']
-        _check_plot_works(radviz, df, 'Name', color=cnames)
+        _check_plot_works(radviz, frame=df, class_column='Name', color=cnames)
         patches = [p for p in ax.patches[:20] if p.get_label() != '']
         self._check_colors(patches, facecolors=cnames, mapping=df['Name'][:10])
 
-        _check_plot_works(radviz, df, 'Name', colormap=cm.jet)
+        _check_plot_works(radviz, frame=df, class_column='Name', colormap=cm.jet)
         cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
         patches = [p for p in ax.patches[:20] if p.get_label() != '']
         self._check_colors(patches, facecolors=cmaps, mapping=df['Name'][:10])
@@ -607,6 +611,8 @@ def test_grouped_plot_fignums(self):
 
     @slow
     def test_grouped_hist_legacy(self):
+        from matplotlib.patches import Rectangle
+
         df = DataFrame(randn(500, 2), columns=['A', 'B'])
         df['C'] = np.random.randint(0, 4, 500)
         df['D'] = ['X'] * 500
@@ -633,7 +639,8 @@ def test_grouped_hist_legacy(self):
                                      xlabelsize=xf, xrot=xrot, ylabelsize=yf, yrot=yrot)
         # height of last bin (index 5) must be 1.0
         for ax in axes.ravel():
-            height = ax.get_children()[5].get_height()
+            rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
+            height = rects[-1].get_height()
             self.assertAlmostEqual(height, 1.0)
         self._check_ticks_props(axes, xlabelsize=xf, xrot=xrot,
                                 ylabelsize=yf, yrot=yrot)

pandas/tools/plotting.py

@@ -24,13 +24,13 @@
 from pandas.compat import range, lrange, lmap, map, zip, string_types
 import pandas.compat as compat
 from pandas.util.decorators import Appender
-
 try:  # mpl optional
     import pandas.tseries.converter as conv
     conv.register()  # needs to override so set_xlim works with str/number
 except ImportError:
     pass
 
+
 # Extracted from https://gist.github.com/huyng/816622
 # this is the rcParams set when setting display.with_mpl_style
 # to True.
@@ -97,6 +97,48 @@
      'ytick.minor.size': 0.0
 }
 
+
+def _mpl_le_1_2_1():
+    try:
+        import matplotlib as mpl
+        return (str(mpl.__version__) <= LooseVersion('1.2.1') and
+                str(mpl.__version__)[0] != '0')
+    except ImportError:
+        return False
+
+def _mpl_ge_1_3_1():
+    try:
+        import matplotlib
+        # The or v[0] == '0' is because their versioneer is
+        # messed up on dev
+        return (matplotlib.__version__ >= LooseVersion('1.3.1')
+                or matplotlib.__version__[0] == '0')
+    except ImportError:
+        return False
+
+def _mpl_ge_1_4_0():
+    try:
+        import matplotlib
+        return (matplotlib.__version__  >= LooseVersion('1.4')
+                or matplotlib.__version__[0] == '0')
+    except ImportError:
+        return False
+
+def _mpl_ge_1_5_0():
+    try:
+        import matplotlib
+        return (matplotlib.__version__  >= LooseVersion('1.5')
+                or matplotlib.__version__[0] == '0')
+    except ImportError:
+        return False
+
+if _mpl_ge_1_5_0():
+    # Compat with mp 1.5, which uses cycler.
+    import cycler
+    colors = mpl_stylesheet.pop('axes.color_cycle')
+    mpl_stylesheet['axes.prop_cycle'] = cycler.cycler('color_cycle', colors)
+
+
 def _get_standard_kind(kind):
     return {'density': 'kde'}.get(kind, kind)
 
@@ -784,7 +826,6 @@ def _kind(self):
     _layout_type = 'vertical'
     _default_rot = 0
     orientation = None
-
     _pop_attributes = ['label', 'style', 'logy', 'logx', 'loglog',
                        'mark_right', 'stacked']
     _attr_defaults = {'logy': False, 'logx': False, 'loglog': False,
@@ -973,8 +1014,9 @@ def _maybe_right_yaxis(self, ax, axes_num):
         else:
             # otherwise, create twin axes
             orig_ax, new_ax = ax, ax.twinx()
-            new_ax._get_lines.color_cycle = orig_ax._get_lines.color_cycle
-
+            # TODO: use Matplotlib public API when available
+            new_ax._get_lines = orig_ax._get_lines
+            new_ax._get_patches_for_fill = orig_ax._get_patches_for_fill
             orig_ax.right_ax, new_ax.left_ax = new_ax, orig_ax
 
             if not self._has_plotted_object(orig_ax):  # no data on left y
@@ -1197,6 +1239,14 @@ def plt(self):
         import matplotlib.pyplot as plt
         return plt
 
+    @staticmethod
+    def mpl_ge_1_3_1():
+        return _mpl_ge_1_3_1()
+
+    @staticmethod
+    def mpl_ge_1_5_0():
+        return _mpl_ge_1_5_0()
+
     _need_to_set_index = False
 
     def _get_xticks(self, convert_period=False):
@@ -1474,9 +1524,6 @@ def __init__(self, data, x, y, s=None, c=None, **kwargs):
         self.c = c
 
     def _make_plot(self):
-        import matplotlib as mpl
-        mpl_ge_1_3_1 = str(mpl.__version__) >= LooseVersion('1.3.1')
-
         x, y, c, data = self.x, self.y, self.c, self.data
         ax = self.axes[0]
 
@@ -1488,9 +1535,13 @@ def _make_plot(self):
         # pandas uses colormap, matplotlib uses cmap.
         cmap = self.colormap or 'Greys'
         cmap = self.plt.cm.get_cmap(cmap)
-
-        if c is None:
+        color = self.kwds.pop("color", None)
+        if c is not None and color is not None:
+            raise TypeError('Specify exactly one of `c` and `color`')
+        elif c is None and color is None:
             c_values = self.plt.rcParams['patch.facecolor']
+        elif color is not None:
+            c_values = color
         elif c_is_column:
             c_values = self.data[c].values
         else:
@@ -1505,7 +1556,7 @@ def _make_plot(self):
         if cb:
             img = ax.collections[0]
             kws = dict(ax=ax)
-            if mpl_ge_1_3_1:
+            if self.mpl_ge_1_3_1():
                 kws['label'] = c if c_is_column else ''
             self.fig.colorbar(img, **kws)
 
@@ -1636,6 +1687,11 @@ def _ts_plot(cls, ax, x, data, style=None, **kwds):
 
         # Set ax with freq info
         _decorate_axes(ax, freq, kwds)
+        # digging deeper
+        if hasattr(ax, 'left_ax'):
+            _decorate_axes(ax.left_ax, freq, kwds)
+        if hasattr(ax, 'right_ax'):
+            _decorate_axes(ax.right_ax, freq, kwds)
         ax._plot_data.append((data, cls._kind, kwds))
 
         lines = cls._plot(ax, data.index, data.values, style=style, **kwds)
@@ -1743,6 +1799,8 @@ def _plot(cls, ax, x, y, style=None, column_num=None,
         if not 'color' in kwds:
             kwds['color'] = lines[0].get_color()
 
+        if cls.mpl_ge_1_5_0(): # mpl 1.5 added real support for poly legends
+            kwds.pop('label')
         ax.fill_between(xdata, start, y_values, **kwds)
         cls._update_stacker(ax, stacking_id, y)
         return lines

pandas/tseries/tests/test_plotting.py

@@ -483,6 +483,7 @@ def test_gaps(self):
         ts[5:25] = np.nan
         ax = ts.plot()
         lines = ax.get_lines()
+        tm._skip_if_mpl_1_5()
         self.assertEqual(len(lines), 1)
         l = lines[0]
         data = l.get_xydata()
@@ -532,6 +533,9 @@ def test_gap_upsample(self):
         self.assertEqual(len(ax.right_ax.get_lines()), 1)
         l = lines[0]
         data = l.get_xydata()
+
+        tm._skip_if_mpl_1_5()
+
         tm.assertIsInstance(data, np.ma.core.MaskedArray)
         mask = data.mask
         self.assertTrue(mask[5:25, 1].all())

pandas/util/testing.py

@@ -196,6 +196,14 @@ def setUpClass(cls):
     return cls
 
 
+def _skip_if_mpl_1_5():
+    import matplotlib
+    v = matplotlib.__version__
+    if v > LooseVersion('1.4.3') or v[0] == '0':
+        import nose
+        raise nose.SkipTest("matplotlib 1.5")
+
+
 def _skip_if_no_scipy():
     try:
         import scipy.stats