Determine datetime_format from more than one element
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd

series_1 = pd.Series(['13/03/2000', '01/03/2000', '02/03/2000'])  # dates in European format
series_2 = pd.Series(['01/03/2000', '13/03/2000', '02/03/2000'])  # same dates, reordered

converted_1 = pd.to_datetime(series_1, infer_datetime_format=True)
converted_2 = pd.to_datetime(series_2, infer_datetime_format=True)

print sorted(series_1) == sorted(series_2)  # True
print sorted(converted_1) == sorted(converted_2)  # False

```
#### Problem description

One would hope to obtain the same result when applying `pd.to_datetime` to the same series twice, but shuffled.

#### Expected Output

My understanding is that the format determined when setting `infer_datetime_format=True` is obtained from the first non-null value of the Series (see function `_guess_datetime_format_for_array` in `tseries.tools`), which explains the result above. I understand this logic in terms of optimizing the operation, and it does work as expected most of the time.
However, I feel like the example provided above is fairly generic. Ideally, the function would find the best `datetime_format` for the entire Series. Any ideas on how to implement this ?

#### Output of ``pd.show_versions()``

<details>INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-57-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.utf8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.19.2
nose: 1.3.7
pip: 9.0.1
setuptools: 28.8.0
Cython: None
numpy: 1.11.3
scipy: 0.18.0
statsmodels: None
xarray: None
IPython: 2.4.1
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.2
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

</details>
