pandas.Timestamp with time only string doesn't work

[ceacar]

Code Sample, a copy-pastable example if possible

In [147]: pandas.Timestamp('4 pm')
---------------------------------------------------------------------------
OutOfBoundsDatetime                       Traceback (most recent call last)
<ipython-input-147-333a3814fcab> in <module>()
----> 1 pandas.Timestamp('4 pm')

pandas/tslib.pyx in pandas.tslib.Timestamp.__new__ (pandas/tslib.c:10447)()

pandas/tslib.pyx in pandas.tslib.convert_to_tsobject (pandas/tslib.c:27555)()

pandas/tslib.pyx in pandas.tslib.convert_str_to_tsobject (pandas/tslib.c:29955)()

pandas/tslib.pyx in pandas.tslib.convert_to_tsobject (pandas/tslib.c:28700)()

pandas/tslib.pyx in pandas.tslib._check_dts_bounds (pandas/tslib.c:32835)()

OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1-01-01 16:00:00

Problem description

this type of string conversion doesn't work with 0.19.2 since upgrade from 0.16.0
traced the problem using git bisect to this commit:
c2ea0d4

Expected Output

In [3]: pandas.Timestamp('4 pm')
Out[3]: Timestamp('2017-04-20 16:00:00')

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 2.7.6.final.0 python-bits: 64 OS: Linux OS-release: 3.13.0-112-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: None.None

pandas: 0.19.2
nose: None
pip: 9.0.1
setuptools: 34.3.3
Cython: None
numpy: 1.11.2
scipy: None
statsmodels: None
xarray: None
IPython: 5.3.0
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.7
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
boto: None
pandas_datareader: None

[jreback]

so the error message is obviously wrong, but what should this actually do? Sure you can return today's date, but generally this indicates an error (and is certainly not explicitly reproducible). I would much rather people be explicit about this.

[jorisvandenbossche]

So the PR on github I linked to seems to be the correct one. As I said there, the PR's intent was to parse something like Timestamp('2012') no longer by filling with current month and day of the month, but setting it to 2012-01-01 (and to make this consistent over the different the different parsing functions we have in pandas).
So that change was certainly intentional. The change that, when only supplying a time part, the date part is no longer filled with the current date, but with 0001-01-01, is possibly a side-effect we maybe didn't fully catch then.

[jorisvandenbossche]

OK, it is not that clear actually, as other time-only string do work:

In [16]: pd.Timestamp("16:15")
Out[16]: Timestamp('2017-04-21 16:15:00')

In [17]: pd.to_datetime("16:15")
Out[17]: Timestamp('2017-04-21 16:15:00')

But, this is a duplicate of #11430, so let's move the discussion over there.