adding mpl jointplot #111

lantern/plotting/__init__.py

@@ -148,7 +148,7 @@ def plot(data, type=None, raw=False, colors=None, **kwargs):
             return getattr(_pm[BACKEND], typ.value)(data, type=typ, colors=colors, **kwargs)
 
         # require more than 1 column
-        if typ in [lookup('pie'), lookup('bubble'), lookup('scatter'), lookup('bar'), lookup('stackedbar'), lookup('horizontalbar'), lookup('horizontalstackedbar'), lookup('box'), lookup('lmplot')]:
+        if typ in [lookup('pie'), lookup('bubble'), lookup('scatter'), lookup('bar'), lookup('stackedbar'), lookup('horizontalbar'), lookup('horizontalstackedbar'), lookup('box'), lookup('lmplot'), lookup('jointplot')]:
             select = [col]
             skip.add(col)
 
@@ -164,7 +164,7 @@ def plot(data, type=None, raw=False, colors=None, **kwargs):
 
             # bubble specific options
             # scatter specific options
-            if typ in [lookup('bubble'), lookup('scatter'), lookup('bubble3d'), lookup('scatter3d'), lookup('lmplot')]:
+            if typ in [lookup('bubble'), lookup('scatter'), lookup('bubble3d'), lookup('scatter3d'), lookup('lmplot'), lookup('jointplot')]:
                 scatter = _parseScatter(kwargs.pop('scatter', {}), col)
                 x = scatter.get('x', col)
                 y = scatter.get('y', col)

lantern/plotting/plot_bokeh.py

@@ -141,6 +141,10 @@ def groupedscatter(data, **kwargs):
     def heatmap(data, **kwargs):
         raise NotImplementedError()
 
+    @staticmethod
+    def jointplot(data, **kwargs):
+        raise NotImplementedError()
+
     @staticmethod
     def lmplot(data, **kwargs):
         raise NotImplementedError()

lantern/plotting/plot_cufflinks.py

@@ -446,6 +446,10 @@ def candlestick(data, **kwargs):
     def density(data, **kwargs):
         raise NotImplementedError()
 
+    @staticmethod
+    def jointplot(data, **kwargs):
+        raise NotImplementedError()
+
     @staticmethod
     def lmplot(data, **kwargs):
         raise NotImplementedError()

lantern/plotting/plot_matplotlib.py

@@ -327,6 +327,20 @@ def horizontalstackedbar(data, **kwargs):
                          stacked=True,
                          **kwargs)
 
+    @staticmethod
+    def jointplot(data, **kwargs):
+        kwargs = MatplotlibPlotMap._wrapper(**kwargs)
+        scatter = kwargs.pop('scatter', {})
+        x = scatter.pop('x', data.columns[0])
+        y = scatter.pop('y', data.columns[0])
+
+        color = kwargs.pop('color')
+        scatter_kws = {'color': kwargs.pop('scatter_color', color)}
+        line_kws = {'color': kwargs.pop('line_color', color)}
+        marginal_kws = {'color': kwargs.pop('bar_color', color)}
+        kind = kwargs.pop('kind', 'reg')
+        return sns.jointplot(x=x, y=y, data=data, kind=kind, scatter_kws=scatter_kws, line_kws=line_kws, marginal_kws=marginal_kws, **kwargs)
+
     @staticmethod
     def line(data, **kwargs):
         ax = MatplotlibPlotMap._newAx(x=False, y=kwargs.get('y', 'left') == 'right', y_side=kwargs.pop('y', 'left'), color=kwargs.get('colors'))

lantern/plotting/plottypes.py

@@ -28,6 +28,7 @@ class BasePlotType(Enum):
     HISTOGRAM = 'histogram'
     HORIZONTALBAR = 'horizontalbar'
     HORIZONTALSTACKEDBAR = 'horizontalstackedbar'
+    JOINTPLOT = 'jointplot'
     LINE = 'line'
     LMPLOT = 'lmplot'
     MULTISCATTER = 'multiscatter'
@@ -130,6 +131,10 @@ def horizontalbar():
     def horizontalstackedbar():
         '''plot type'''
 
+    @abstractmethod
+    def jointplot():
+        '''plot type'''
+
     @abstractstatic
     def line():
         '''plot type'''

tests/plot/test_plot_matplotlib.py

@@ -128,6 +128,15 @@ def test_lmplot(self):
             df = line.sample()
             plot(df[[df.columns[0], df.columns[1]]], type='lmplot', scatter={df.columns[0]: {'x': df.columns[0], 'y': df.columns[1]}})
 
+    def test_jointplot(self):
+        with patch('lantern.plotting.plot_matplotlib.in_ipynb', create=True) as mock1:
+            from lantern.plotting import setBackend
+            from lantern import line, plot
+            mock1.return_value = True
+            setBackend('matplotlib')
+            df = line.sample()
+            plot(df[[df.columns[0], df.columns[1]]], type='jointplot', scatter={df.columns[0]: {'x': df.columns[0], 'y': df.columns[1]}})
+
     def test_probplot(self):
         with patch('lantern.plotting.plot_matplotlib.in_ipynb', create=True) as mock1:
             from lantern.plotting import setBackend