Datetimes are inconsistently truncated in to_csv
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
df = pd.DataFrame({
    'date': pd.to_datetime('1970-01-01'),
    'datetime': pd.date_range('1970-01-01', periods=5, freq='H')
})
df['date'].to_csv('/dev/stdout', index=False)
df[['date', 'datetime']].to_csv('/dev/stdout', index=False)
```

```
date
1970-01-01
1970-01-01
1970-01-01
1970-01-01
1970-01-01

date,datetime
1970-01-01 00:00:00,1970-01-01 00:00:00
1970-01-01 00:00:00,1970-01-01 01:00:00
1970-01-01 00:00:00,1970-01-01 02:00:00
1970-01-01 00:00:00,1970-01-01 03:00:00
1970-01-01 00:00:00,1970-01-01 04:00:00
```

#### Problem description

datetime64 series with all `00:00:00` time components are written out in inconsistent formats depending on the inclusion of time in _other_ datetime64 series within the dataframe. I expected series with `00:00:00` times to be trimmed on a per-series basis, regardless of the inclusion of other Series with populated times. Per-series formatting would be better because the results become more independent and intuitive.

This makes testing more brittle because changes in one series (or adding a timed series to a df) have side effects for other series' output.

I have output CSVs that are then loaded into another system that expects date types in some columns and datetimes in others, which then fails to load because the date only columns have ` 00:00:00` included. Currently, I track internal column metadata and `.dt.strftime('%Y-%m-%d').map(lambda x: x != 'NaT' and x or None)` the date columns to get around the formatting.

#### Expected Output

```
# df[['date', 'datetime']].to_csv('/dev/stdout', index=False)
date,datetime
1970-01-01,1970-01-01 00:00:00
1970-01-01,1970-01-01 01:00:00
1970-01-01,1970-01-01 02:00:00
1970-01-01,1970-01-01 03:00:00
1970-01-01,1970-01-01 04:00:00
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Darwin
OS-release: 17.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.1
pytest: None
pip: 10.0.1
setuptools: 39.1.0
Cython: None
numpy: 1.14.3
scipy: None
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
