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: c2ea0d4d1f7333dfb5f35d0795267d8894a37d83

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

Comment From: 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.

Comment From: 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.

Comment From: 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 https://github.com/pandas-dev/pandas/issues/11430, so let's move the discussion over there.