DOC/BUG: pd.to_datetime example produces different results from documentation

[AnkurDedania]

A small, complete example of the issue

referring too http://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html

The example provides different results.

# Your code here
import pandas as pd
pd.to_datetime('13000101', format='%Y%m%d')

raises...

Traceback (most recent call last):
  File "C:\Miniconda3\lib\site-packages\pandas\tseries\tools.py", line 404, in _convert_listlike
    values, tz = tslib.datetime_to_datetime64(arg)
  File "pandas\tslib.pyx", line 1754, in pandas.tslib.datetime_to_datetime64 (pandas\tslib.c:30557)
TypeError: Unrecognized value type: <class 'str'>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Miniconda3\lib\site-packages\pandas\util\decorators.py", line 91, in wrapper
    return func(*args, **kwargs)
  File "C:\Miniconda3\lib\site-packages\pandas\tseries\tools.py", line 424, in to_datetime
    return _convert_listlike(np.array([arg]), box, format)[0]
  File "C:\Miniconda3\lib\site-packages\pandas\tseries\tools.py", line 407, in _convert_listlike
    raise e
  File "C:\Miniconda3\lib\site-packages\pandas\tseries\tools.py", line 374, in _convert_listlike
    errors=errors)
  File "pandas\tslib.pyx", line 3721, in pandas.tslib.array_strptime (pandas\tslib.c:60980)
  File "pandas\tslib.pyx", line 3716, in pandas.tslib.array_strptime (pandas\tslib.c:60878)
  File "pandas\tslib.pyx", line 1718, in pandas.tslib._check_dts_bounds (pandas\tslib.c:30034)
pandas.tslib.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1300-01-01 00:00:00

Expected Output

(according to example in docs)

datetime.datetime(1300, 1, 1, 0, 0)

Output of pd.show_versions()

pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 63 Stepping 2, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.19.0
nose: 1.3.7
pip: 8.1.2
setuptools: 28.0.0
Cython: 0.24.1
numpy: 1.11.2
scipy: 0.18.1
statsmodels: 0.6.1
xarray: 0.8.2
IPython: 5.1.0
sphinx: 1.4.8
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.7
blosc: 1.4.1
bottleneck: 1.1.0
tables: None
numexpr: 2.6.0
matplotlib: 1.5.3
openpyxl: 2.4.0
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.0
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.1.0
pymysql: 0.7.9.None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None

[chris-b1]

I'm guessing this was a side effect of #10674. I'm actually in favor of the new behavior - makes it much more obvious there is a problem, but I suppose this behavior might have been useful in some cases.

[jreback]

the doc-string needs to be updated to use ignore

In [2]: import pandas as pd
   ...: pd.to_datetime('13000101', format='%Y%m%d',errors='ignore')
Out[2]: datetime.datetime(1300, 1, 1, 0, 0)

[chris-b1]

@jreback - oh, I see, I had tried without the format, which I guess never returned a plain datetime, so agree it's just docs

In [26]: pd.to_datetime('13000101', errors='ignore')
Out[26]: '13000101'

[jorisvandenbossche]

It is a bit inconsistent that the return type changes on whether format is specified or not:

In [1]: pd.to_datetime('13000101', errors='ignore')
Out[1]: '13000101'

In [2]: pd.to_datetime('13000101', errors='ignore', format='%Y%m%d')
Out[2]: datetime.datetime(1300, 1, 1, 0, 0)