diff --git a/pandas/tseries/tests/test_period.py b/pandas/tseries/tests/test_period.py index 1ddcc11c15a59..468c3d5bfc37c 100644 --- a/pandas/tseries/tests/test_period.py +++ b/pandas/tseries/tests/test_period.py @@ -2180,6 +2180,13 @@ def test_getitem_nat(self): pd.Period('2011-01', freq='M')) self.assertIs(s[pd.NaT], tslib.NaT) + def test_getitem_list_periods(self): + # GH 7710 + rng = period_range(start='2012-01-01', periods=10, freq='D') + ts = Series(lrange(len(rng)), index=rng) + exp = ts.iloc[[1]] + tm.assert_series_equal(ts[[Period('2012-01-02', freq='D')]], exp) + def test_slice_with_negative_step(self): ts = Series(np.arange(20), period_range('2014-01', periods=20, freq='M')) diff --git a/pandas/tseries/tests/test_resample.py b/pandas/tseries/tests/test_resample.py index 49802ba640d70..48e13518ad2a2 100644 --- a/pandas/tseries/tests/test_resample.py +++ b/pandas/tseries/tests/test_resample.py @@ -1952,6 +1952,23 @@ def test_resample_timedelta_values(self): res = df['time'].resample('2D').first() tm.assert_series_equal(res, exp) + def test_resample_datetime_values(self): + # GH 13119 + # check that datetime dtype is preserved when NaT values are + # introduced by the resampling + + dates = [datetime(2016, 1, 15), datetime(2016, 1, 19)] + df = DataFrame({'timestamp': dates}, index=dates) + + exp = Series([datetime(2016, 1, 15), pd.NaT, datetime(2016, 1, 19)], + index=date_range('2016-01-15', periods=3, freq='2D'), + name='timestamp') + + res = df.resample('2D').first()['timestamp'] + tm.assert_series_equal(res, exp) + res = df['timestamp'].resample('2D').first() + tm.assert_series_equal(res, exp) + class TestPeriodIndex(Base, tm.TestCase): _multiprocess_can_split_ = True diff --git a/pandas/tseries/tests/test_timeseries.py b/pandas/tseries/tests/test_timeseries.py index 5eb46684d1860..2355d663ed7d5 100644 --- a/pandas/tseries/tests/test_timeseries.py +++ b/pandas/tseries/tests/test_timeseries.py @@ -4400,6 +4400,14 @@ def test_intercept_astype_object(self): result = df.values.squeeze() self.assertTrue((result[:, 0] == expected.values).all()) + def test_nat_operations(self): + # GH 8617 + s = Series([0, pd.NaT], dtype='m8[ns]') + exp = s[0] + self.assertEqual(s.median(), exp) + self.assertEqual(s.min(), exp) + self.assertEqual(s.max(), exp) + class TestTimestamp(tm.TestCase): def test_class_ops_pytz(self):