No way with to_json to write only date out of datetime
#### Code Sample, a copy-pastable example if possible

```python
In [2]: pd.Series(pd.to_datetime(['2017-03-15'])).to_csv()
Out[2]: '0,2017-03-15\n'

In [3]: pd.Series(pd.to_datetime(['2017-03-15'])).to_json(date_format='iso')
Out[3]: '{"0":"2017-03-15T00:00:00.000Z"}'
```
#### Problem description

From [this SO comment](https://stackoverflow.com/questions/16176996/keep-only-date-part-when-using-pandas-to-datetime/41718815?noredirect=1#comment75167203_41718815)

By default, ``to_csv()`` drops times of day if they are all midnight. By default, ``to_json`` instead writes dates in epoch, but if passed ``date_format='iso'`` will always write times.

Not sure whether it would be optimal to have ``date_format='iso'`` behave as ``to_csv()``, or rather add a new (for instance) ``date_format='iso_date'``, or maybe even free-form like accepted by ``pd.Series.df.strftime()``, e.g. ``date_format="%Y-%m-%d"``.

#### Expected Output
```python
Out[3]: '{"0":"2017-03-15"}'
```

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

<details>
# Paste the output here pd.shoINSTALLED VERSIONS
------------------
commit: None
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.7.0-1-amd64
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: it_IT.utf8
LOCALE: it_IT.UTF-8

pandas: 0.20.1
pytest: 3.0.6
pip: 9.0.1
setuptools: None
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: 0.9.2
IPython: 5.1.0.dev
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.0.2
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.6
lxml: 3.7.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: 0.2.1
w_versions() here

</details>
