BUG: allow numpy.array as c values to scatterplot

Ensure that we can pass an np.array as 'c' straight through to
matplotlib, this functionality was accidentally removed previously.

Add tests.

Closes #8852

Author: aevri

doc/source/whatsnew/v0.15.2.txt

@@ -156,6 +156,11 @@ Bug Fixes
   and the last offset is not calculated from the start of the range (:issue:`8683`)
 
 
+
+- Bug where DataFrame.plot(kind='scatter') fails when checking if an np.array is in the DataFrame (:issue:`8852`)
+
+
+
 - Bug in `pd.infer_freq`/`DataFrame.inferred_freq` that prevented proper sub-daily frequency inference
   when the index contained DST days (:issue:`8772`).
 - Bug where index name was still used when plotting a series with ``use_index=False`` (:issue:`8558`).

pandas/tests/test_graphics.py

@@ -1645,6 +1645,31 @@ def test_plot_scatter_with_c(self):
         self.assertIs(ax.collections[0].colorbar, None)
         self._check_colors(ax.collections, facecolors=['r'])
 
+        # Ensure that we can pass an np.array straight through to matplotlib,
+        # this functionality was accidentally removed previously.
+        # See https://github.com/pydata/pandas/issues/8852 for bug report
+        #
+        # Exercise colormap path and non-colormap path as they are independent
+        #
+        df = DataFrame({'A': [1, 2], 'B': [3, 4]})
+        red_rgba = [1.0, 0.0, 0.0, 1.0]
+        green_rgba = [0.0, 1.0, 0.0, 1.0]
+        rgba_array = np.array([red_rgba, green_rgba])
+        ax = df.plot(kind='scatter', x='A', y='B', c=rgba_array)
+        # expect the face colors of the points in the non-colormap path to be
+        # identical to the values we supplied, normally we'd be on shaky ground
+        # comparing floats for equality but here we expect them to be
+        # identical.
+        self.assertTrue(
+            np.array_equal(
+                ax.collections[0].get_facecolor(),
+                rgba_array))
+        # we don't test the colors of the faces in this next plot because they
+        # are dependent on the spring colormap, which may change its colors
+        # later.
+        float_array = np.array([0.0, 1.0])
+        df.plot(kind='scatter', x='A', y='B', c=float_array, cmap='spring')
+
     @slow
     def test_plot_bar(self):
         df = DataFrame(randn(6, 4),

pandas/tools/plotting.py

@@ -1403,16 +1403,18 @@ def _make_plot(self):
         x, y, c, data = self.x, self.y, self.c, self.data
         ax = self.axes[0]
 
+        c_is_column = com.is_hashable(c) and c in self.data.columns
+
         # plot a colorbar only if a colormap is provided or necessary
-        cb = self.kwds.pop('colorbar', self.colormap or c in self.data.columns)
+        cb = self.kwds.pop('colorbar', self.colormap or c_is_column)
 
         # pandas uses colormap, matplotlib uses cmap.
         cmap = self.colormap or 'Greys'
         cmap = plt.cm.get_cmap(cmap)
 
         if c is None:
             c_values = self.plt.rcParams['patch.facecolor']
-        elif c in self.data.columns:
+        elif c_is_column:
             c_values = self.data[c].values
         else:
             c_values = c
@@ -1427,7 +1429,7 @@ def _make_plot(self):
             img = ax.collections[0]
             kws = dict(ax=ax)
             if mpl_ge_1_3_1:
-                kws['label'] = c if c in self.data.columns else ''
+                kws['label'] = c if c_is_column else ''
             self.fig.colorbar(img, **kws)
 
         self._add_legend_handle(scatter, label)