TST: Add lineplot tests with unsorted x data

Two new tests check interaction of non-monotonic x data and xlims:
test_frame / test_unsorted_index_lims
test_series / test_unsorted_index_xlim

Author: nmartensen

pandas/tests/plotting/test_frame.py

@@ -301,6 +301,29 @@ def test_unsorted_index(self):
         rs = Series(rs[:, 1], rs[:, 0], dtype=np.int64, name='y')
         tm.assert_series_equal(rs, df.y)
 
+    def test_unsorted_index_lims(self):
+        df = DataFrame({'y': [0., 1., 2., 3.]}, index=[1., 0., 3., 2.])
+        ax = df.plot()
+        xmin, xmax = ax.get_xlim()
+        lines = ax.get_lines()
+        assert xmin <= np.nanmin(lines[0].get_data()[0])
+        assert xmax >= np.nanmax(lines[0].get_data()[0])
+
+        df = DataFrame({'y': [0., 1., np.nan, 3., 4., 5., 6.]},
+                       index=[1., 0., 3., 2., np.nan, 3., 2.])
+        ax = df.plot()
+        xmin, xmax = ax.get_xlim()
+        lines = ax.get_lines()
+        assert xmin <= np.nanmin(lines[0].get_data()[0])
+        assert xmax >= np.nanmax(lines[0].get_data()[0])
+
+        df = DataFrame({'y': [0., 1., 2., 3.], 'z': [91., 90., 93., 92.]})
+        ax = df.plot(x='z', y='y')
+        xmin, xmax = ax.get_xlim()
+        lines = ax.get_lines()
+        assert xmin <= np.nanmin(lines[0].get_data()[0])
+        assert xmax >= np.nanmax(lines[0].get_data()[0])
+
     @slow
     def test_subplots(self):
         df = DataFrame(np.random.rand(10, 3),

pandas/tests/plotting/test_series.py

@@ -280,6 +280,16 @@ def test_irregular_datetime(self):
         ax.set_xlim('1/1/1999', '1/1/2001')
         assert xp == ax.get_xlim()[0]
 
+    def test_unsorted_index_xlim(self):
+        ser = Series([0., 1., np.nan, 3., 4., 5., 6.],
+                     index=[1., 0., 3., 2., np.nan, 3., 2.])
+        _, ax = self.plt.subplots()
+        ax = ser.plot(ax=ax)
+        xmin, xmax = ax.get_xlim()
+        lines = ax.get_lines()
+        assert xmin <= np.nanmin(lines[0].get_data(orig=False)[0])
+        assert xmax >= np.nanmax(lines[0].get_data(orig=False)[0])
+
     @slow
     def test_pie_series(self):
         # if sum of values is less than 1.0, pie handle them as rate and draw