to_datetime returns NaT for old dates with coerce=True

[vfilimonov]

When use coerce=True in pandas.to_datetime old dates (before 1677-09-22) return NaT. The same dates without coerce are parsed correctly:

print pd.to_datetime('13000101', format='%Y%m%d', coerce=True)
print pd.to_datetime('13000101', format='%Y%m%d')

returns

NaT
1300-01-01 00:00:00

pandas: 0.15.2
numpy: 1.9.1

[shoyer]

I believe this is intentional, although it is poorly documented. The return value in the second case is a datetime.datetime object rather than a pandas.Timestamp object. @jreback thoughts?

[shoyer]

To be clear, this (old dates) is a case where to_datetime cannot turn the date into a Timestamp, which is the normal result. So it's a choice (controlled here by coerce) between returning a pandas compatible NaT object or plain python datetime object.

[jreback]

this is correct, the 2nd is a datetime.datetime (Timestamp is a sub-class of this).

not a bug. let's turn this to a further update to the docs (see #8921).

@vfilimonov want to do this?

[miggec]

as of 1.0.0-dev this looks to be resolved:

pd.to_datetime('13000101', format='%Y%m%d')

...

~/pandas-squigmig/pandas/core/tools/datetimes.py in _convert_listlike_datetimes(arg, box, format, name, tz, unit, errors, infer_datetime_format, dayfirst, yearfirst, exact)
    412                 try:
    413                     result, timezones = array_strptime(
--> 414                         arg, format, exact=exact, errors=errors
    415                     )
    416                     if "%Z" in format or "%z" in format:

~/pandas-squigmig/pandas/_libs/tslibs/strptime.pyx in pandas._libs.tslibs.strptime.array_strptime()
    335                 iresult[i] = NPY_NAT
    336                 continue
--> 337             raise
    338 
    339         result_timezone[i] = timezone

~/pandas-squigmig/pandas/_libs/tslibs/strptime.pyx in pandas._libs.tslibs.strptime.array_strptime()
    330         iresult[i] = dtstruct_to_dt64(&dts)
    331         try:
--> 332             check_dts_bounds(&dts)
    333         except ValueError:
    334             if is_coerce:

~/pandas-squigmig/pandas/_libs/tslibs/np_datetime.pyx in pandas._libs.tslibs.np_datetime.check_dts_bounds()
    116                                                dts.day, dts.hour,
    117                                                dts.min, dts.sec)
--> 118         raise OutOfBoundsDatetime(
    119             'Out of bounds nanosecond timestamp: {fmt}'.format(fmt=fmt))
    120 

OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1300-01-01 00:00:00