BUG: Handle iterable of arrays in convert

DatetimeConverter.convert can take an array or iterable of arrays.
Fixed the converter to detect which case we're in and then re-use
the existing logic.

Author: TomAugspurger

pandas/plotting/_converter.py

@@ -16,7 +16,9 @@
     is_integer_dtype,
     is_float_dtype,
     is_datetime64_ns_dtype,
-    is_period_arraylike)
+    is_period_arraylike,
+    is_list_like
+)
 
 from pandas.compat import lrange
 import pandas.compat as compat
@@ -178,6 +180,16 @@ class DatetimeConverter(dates.DateConverter):
 
     @staticmethod
     def convert(values, unit, axis):
+        # values might be a 1-d array, or a list-like of arrays.
+        if is_list_like(values) and is_list_like(values[0]):
+            values = [DatetimeConverter._convert_1d(v, unit, axis)
+                      for v in values]
+        else:
+            values = DatetimeConverter._convert_1d(values, unit, axis)
+        return values
+
+    @staticmethod
+    def _convert_1d(values, unit, axis):
         def try_parse(values):
             try:
                 return _dt_to_float_ordinal(tools.to_datetime(values))

pandas/tests/plotting/test_datetimelike.py

@@ -1332,6 +1332,15 @@ def test_timedelta_plot(self):
         s = Series(np.random.randn(len(index)), index)
         _check_plot_works(s.plot)
 
+    def test_hist(self):
+        # https://github.com/matplotlib/matplotlib/issues/8459
+        rng = date_range('1/1/2011', periods=10, freq='H')
+
+        x = rng
+        w1 = np.arange(0, 1, .1)
+        w2 = np.arange(0, 1, .1)[::-1]
+        self.plt.hist([x, x], weights=[w1, w2])
+
 
 def _check_plot_works(f, freq=None, series=None, *args, **kwargs):
     import matplotlib.pyplot as plt