In [16]: i = pd.date_range('20130101', periods=3, tz='US/Eastern') In [17]: i2 = pd.Index([pd.NaT, pd.NaT] + i[2:].tolist()) In [18]: i.where(pd.notna(i2), i2) Out[18]: DatetimeIndex(['NaT', 'NaT', '2013-01-03 00:00:00-05:00'], dtype='datetime64[ns, US/Eastern]', freq='D')

In [23]: result._eadata._validate_frequency(result, result.freq) --------------------------------------------------------------------------- ValueError Traceback (most recent call last) ~/sandbox/pandas-alt/pandas/core/arrays/datetimelike.py in _validate_frequency(cls, index, freq, **kwargs) 863 periods=len(index), freq=freq, --> 864 **kwargs) 865 if not np.array_equal(index.asi8, on_freq.asi8): ~/sandbox/pandas-alt/pandas/core/arrays/datetimes.py in _generate_range(cls, start, end, periods, freq, tz, normalize, ambiguous, nonexistent, closed) 299 if start is NaT or end is NaT: --> 300 raise ValueError("Neither `start` nor `end` can be NaT") 301 ValueError: Neither `start` nor `end` can be NaT During handling of the above exception, another exception occurred: ValueError Traceback (most recent call last) <ipython-input-23-24fa3f452eb0> in <module> ----> 1 result._eadata._validate_frequency(result, result.freq) ~/sandbox/pandas-alt/pandas/core/arrays/datetimelike.py in _validate_frequency(cls, index, freq, **kwargs) 877 raise ValueError('Inferred frequency {infer} from passed values ' 878 'does not conform to passed frequency {passed}' --> 879 .format(infer=inferred, passed=freq.freqstr)) 880 881 # monotonicity/uniqueness properties are called via frequencies.infer_freq, ValueError: Inferred frequency None from passed values does not conform to passed frequency D