BUG: median() not correctly handling non-float null values (fixes #10040)

Author: mortada

pandas/core/nanops.py

@@ -285,6 +285,7 @@ def get_median(x):
 
  if values.dtype != np.float64:
  values = values.astype('f8')
+ values[mask] = np.nan
 
  if axis is None:
  values = values.ravel()

pandas/tseries/tests/test_timedeltas.py

@@ -614,7 +614,7 @@ def test_timedelta_ops(self):
  self.assertEqual(result, expected)
 
  result = td.median()
- expected = to_timedelta('00:00:08')
+ expected = to_timedelta('00:00:09')
  self.assertEqual(result, expected)
 
  result = td.to_frame().median()
@@ -641,6 +641,14 @@ def test_timedelta_ops(self):
  for op in ['skew','kurt','sem','var','prod']:
  self.assertRaises(TypeError, lambda : getattr(td,op)())
 
+ # GH 10040
+ # make sure NaT is properly handled by median()
+ s = Series([Timestamp('2015-02-03'), Timestamp('2015-02-07')])
+ self.assertEqual(s.diff().median(), timedelta(days=4))
+
+ s = Series([Timestamp('2015-02-03'), Timestamp('2015-02-07'), Timestamp('2015-02-15')])
+ self.assertEqual(s.diff().median(), timedelta(days=6))
+
  def test_timedelta_ops_scalar(self):
  # GH 6808
  base = pd.to_datetime('20130101 09:01:12.123456')