VIS: let PeriodConverter handle datetime64 data (#18468)

Author: jorisvandenbossche

pandas/plotting/_converter.py

@@ -244,7 +244,7 @@ def _convert_1d(values, units, axis):
         if not hasattr(axis, 'freq'):
             raise TypeError('Axis must have `freq` set to convert to Periods')
         valid_types = (compat.string_types, datetime,
-                       Period, pydt.date, pydt.time)
+                       Period, pydt.date, pydt.time, np.datetime64)
         if (isinstance(values, valid_types) or is_integer(values) or
                 is_float(values)):
             return get_datevalue(values, axis.freq)
@@ -263,7 +263,7 @@ def get_datevalue(date, freq):
     if isinstance(date, Period):
         return date.asfreq(freq).ordinal
     elif isinstance(date, (compat.string_types, datetime,
-                           pydt.date, pydt.time)):
+                           pydt.date, pydt.time, np.datetime64)):
         return Period(date, freq).ordinal
     elif (is_integer(date) or is_float(date) or
           (isinstance(date, (np.ndarray, Index)) and (date.size == 1))):

pandas/tests/plotting/test_converter.py

@@ -327,21 +327,19 @@ def test_conversion(self):
         rs = self.pc.convert(Timestamp('2012-1-1'), None, self.axis)
         assert rs == xp
 
-        # FIXME
-        # rs = self.pc.convert(
-        #        np_datetime64_compat('2012-01-01'), None, self.axis)
-        # assert rs == xp
-        #
-        # rs = self.pc.convert(
-        #        np_datetime64_compat('2012-01-01 00:00:00+0000'),
-        #                      None, self.axis)
-        # assert rs == xp
-        #
-        # rs = self.pc.convert(np.array([
-        #     np_datetime64_compat('2012-01-01 00:00:00+0000'),
-        #     np_datetime64_compat('2012-01-02 00:00:00+0000')]),
-        #                          None, self.axis)
-        # assert rs[0] == xp
+        rs = self.pc.convert(
+            np_datetime64_compat('2012-01-01'), None, self.axis)
+        assert rs == xp
+
+        rs = self.pc.convert(
+            np_datetime64_compat('2012-01-01 00:00:00+0000'), None, self.axis)
+        assert rs == xp
+
+        rs = self.pc.convert(np.array([
+            np_datetime64_compat('2012-01-01 00:00:00+0000'),
+            np_datetime64_compat('2012-01-02 00:00:00+0000')]),
+            None, self.axis)
+        assert rs[0] == xp
 
     def test_integer_passthrough(self):
         # GH9012

pandas/tests/plotting/test_datetimelike.py

@@ -1449,6 +1449,19 @@ def test_overlapping_datetime(self):
         s2.plot(ax=ax)
         s1.plot(ax=ax)
 
+    @pytest.mark.xfail(reason="GH9053 matplotlib does not use"
+                              " ax.xaxis.converter")
+    def test_add_matplotlib_datetime64(self):
+        # GH9053 - ensure that a plot with PeriodConverter still understands
+        # datetime64 data. This still fails because matplotlib overrides the
+        # ax.xaxis.converter with a DatetimeConverter
+        s = Series(np.random.randn(10),
+                   index=date_range('1970-01-02', periods=10))
+        ax = s.plot()
+        ax.plot(s.index, s.values, color='g')
+        l1, l2 = ax.lines
+        tm.assert_numpy_array_equal(l1.get_xydata(), l2.get_xydata())
+
 
 def _check_plot_works(f, freq=None, series=None, *args, **kwargs):
     import matplotlib.pyplot as plt