BUG: Passing datetime strings of the form "1-01-01 00:00:00"

[znicholls]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

---

Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

>>> import pandas as pd
>>> pd.Timestamp("1-01-01 00:00:00")
Timestamp('2001-01-01 00:00:00')

Problem description

Passing "1-01-01 00:00:00" to "2001-01-01 00:00:00" is clearly wrong, this should raise an out of bounds datetime error.

Expected Output

>>> import pandas as pd
>>> pd.Timestamp("1-01-01 00:00:00")
OutOfBoundsDatetime

However, the problem here appears to be deeper than pandas, specifically

>>> from dateutil import parser
>>> parser.parse("1-01-01 00:00:00")
datetime.datetime(2001, 1, 1, 0, 0)

If it's helpful, I'm happy to raise an issue in https://github.com/dateutil/dateutil instead. It's not super clear to me where the error really is (maybe dateutil have a very good reason for parsing "1-01-01 00:00:00" as "2001-01-01 00:00:00").

Output of pd.show_versions()

pd.show_versions()

INSTALLED VERSIONS

commit : cd88ee2
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
Version : Darwin Kernel Version 18.7.0: Mon Aug 31 20:53:32 PDT 2020; root:xnu-4903.278.44~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_AU.UTF-8
LOCALE : en_AU.UTF-8

pandas : 1.2.0.dev0+746.gcd88ee2dd
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.3
setuptools : 49.1.0.post20200704
Cython : 0.29.21
pytest : 6.1.1
hypothesis : 5.37.1
sphinx : 3.2.1
blosc : None
feather : None
xlsxwriter : 1.3.6
lxml.etree : 4.5.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 0.8.3
fastparquet : 0.4.0
gcsfs : 0.7.1
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.5
pandas_gbq : None
pyarrow : 0.17.1
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.5.1
sqlalchemy : 1.3.19
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.15.1
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.48.0

[znicholls]

I have put a failing test in #37070 in case that is helpful

[jorisvandenbossche]

We indeed rely here on the behaviour of dateutil.

Note that specifying the year as 4 numbers gives the expected result:

In [21]: pd.Timestamp("0001-01-01 00:00:00")
...
OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1-01-01 00:00:00

Funny (or ironic ..) thing is that the error message actually shows the datetime in the format you are using / doesn't work.

I was going to say that if you don't want to rely on "inferring" the date from dateutil, you should pass a format string to ensure you have always consistent parsing (https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes). But, I don't seem to find how to specify the format for a year like "1" (both %Y and %y expect zero-padded years)

[znicholls]

We indeed rely here on the behaviour of dateutil

Ok in that case I'll add an issue in that repo and let's see what happens.

[znicholls]

Ok in that case I'll add an issue in that repo and let's see what happens

Having thought about it more and looked through dateutil, it is indeed ambiguous (e.g. 2-03-04 could be 2nd March year 4 or 2nd March 2004 or 4th March year 2) so I'll go up the chain instead to where this originally arose (xarray). Thanks for your help @jorisvandenbossche 👍