BUG: allow numpy.array as c values to scatterplot

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/core/common.py

@@ -2504,6 +2504,38 @@ def is_list_like(arg):
             not isinstance(arg, compat.string_and_binary_types))
 
 
+def is_hashable(arg):
+    """Return True if hash(arg) will succeed, False otherwise.
+
+    Some types will pass a test against collections.Hashable but fail when they
+    are actually hashed with hash().
+
+    Distinguish between these and other types by trying the call to hash() and
+    seeing if they raise TypeError.
+
+    Examples
+    --------
+    >>> a = ([],)
+    >>> isinstance(a, collections.Hashable)
+    True
+    >>> is_hashable(a)
+    False
+    """
+    # don't consider anything not collections.Hashable, so as not to broaden
+    # the definition of hashable beyond that. For example, old-style classes
+    # are not collections.Hashable but they won't fail hash().
+    if not isinstance(arg, collections.Hashable):
+        return False
+
+    # narrow the definition of hashable if hash(arg) fails in practice
+    try:
+        hash(arg)
+    except TypeError:
+        return False
+    else:
+        return True
+
+
 def is_sequence(x):
     try:
         iter(x)

pandas/tests/test_common.py

@@ -1,5 +1,7 @@
+import collections
 from datetime import datetime
 import re
+import sys
 
 import nose
 from nose.tools import assert_equal
@@ -398,6 +400,55 @@ def test_is_list_like():
         assert not com.is_list_like(f)
 
 
+def test_is_hashable():
+
+    # all new-style classes are hashable by default
+    class HashableClass(object):
+        pass
+
+    class UnhashableClass1(object):
+        __hash__ = None
+
+    class UnhashableClass2(object):
+        def __hash__(self):
+            raise TypeError("Not hashable")
+
+    hashable = (
+        1, 'a', tuple(), (1,), HashableClass(),
+    )
+    not_hashable = (
+        [], UnhashableClass1(),
+    )
+    abc_hashable_not_really_hashable = (
+        ([],), UnhashableClass2(),
+    )
+
+    for i in hashable:
+        assert isinstance(i, collections.Hashable)
+        assert com.is_hashable(i)
+    for i in not_hashable:
+        assert not isinstance(i, collections.Hashable)
+        assert not com.is_hashable(i)
+    for i in abc_hashable_not_really_hashable:
+        assert isinstance(i, collections.Hashable)
+        assert not com.is_hashable(i)
+
+    # numpy.array is no longer collections.Hashable as of
+    # https://github.com/numpy/numpy/pull/5326, just test
+    # pandas.common.is_hashable()
+    assert not com.is_hashable(np.array([]))
+
+    # old-style classes in Python 2 don't appear hashable to
+    # collections.Hashable but also seem to support hash() by default
+    if sys.version_info[0] == 2:
+        class OldStyleClass():
+            pass
+        c = OldStyleClass()
+        assert not isinstance(c, collections.Hashable)
+        assert not com.is_hashable(c)
+        hash(c)  # this will not raise
+
+
 def test_ensure_int32():
     values = np.arange(10, dtype=np.int32)
     result = com._ensure_int32(values)

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)