Converting float64 values to datetime64[ns] format using pd.to_datetime results in NaT if errors='coerce'
#### Code Sample, a copy-pastable example if possible

A Pandas dataframe contains a date variable that is formatted as float64 as follows:

```
tempDF = pd.DataFrame({'group': ['a','b'],
                       'date': [1.434692e+18,1.432766e+18]})

print(tempDF)
```

Which appears as:

```
           date group
0  1.434692e+18     a
1  1.432766e+18     b
```

The date variables can be formatted to datetime64[ns] as follows:

```
tempDF['date'] = pd.to_datetime(tempDF['date'],format=None)
print(tempDF)
```

Which works as expected:

```
                 date group
0 2015-06-19 05:33:20     a
1 2015-05-27 22:33:20     b
```

However, if errors='coerce' is included in the do_datetime() function, the dates are returned as NaT.

```
tempDF['date'] = pd.to_datetime(tempDF['date'],format=None,errors='coerce')
print(tempDF)
```

Which produces the following:

```
  date group
0  NaT     a
1  NaT     b
```

This issue was identified as a result of a reported bug (#12821 ) where datetime64[ns] columns are returned as float64 following agg() function where all dates in a group are NaT. Converting columns back to datetime64[ns] format is necessary. However, identifying valid numeric values as errors when errors='coerce' and returning NaT values results in unnecessary data-loss.
#### Expected Output

```
                 date group
0 2015-06-19 05:33:20     a
1 2015-05-27 22:33:20     b
```
#### output of `pd.show_versions()`

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.1.final.0
python-bits: 64
OS: Darwin
OS-release: 15.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8

pandas: 0.18.1
nose: None
pip: 1.5.6
setuptools: 20.1.1
Cython: None
numpy: 1.11.0
scipy: 0.16.1
statsmodels: None
xarray: None
IPython: 4.1.1
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.0
openpyxl: 2.3.2
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None
```
