plt.xticks after plotting with DateTimeIndex results in strange labels
#### Code Sample, a copy-pastable example if possible

```python
N = 10
idx = pd.DatetimeIndex(['2015-{}-01'.format(i) for i in range(1, N+1)])
pd.Series(range(10), idx).plot()
```
results in the following:
[ex1](https://user-images.githubusercontent.com/1224492/34227782-b17faa7c-e5ce-11e7-93bc-122bfc719700.png)

In order to remove some labels on the x axis, I do
```python
plt.xticks(['2015-{}-01'.format(i) for i in range(1, N+1, 3)], fontsize=16)
```
... but the following happens:

![ex2](https://user-images.githubusercontent.com/1224492/34227838-df3bd1de-e5ce-11e7-8280-ed8d541a492d.png)

So I think "pandas formatter doesn't like to be customized, fine", and I add
```python
plt.gca().xaxis.set_major_formatter(DateFormatter('%Y-%m'))
```
and I get
![ex3](https://user-images.githubusercontent.com/1224492/34227876-04188e2a-e5cf-11e7-9623-d824143b709d.png)

If instead I directly plot with matplotlib:
```python
plt.plot(idx, range(10))
plt.xticks(['2015-{}-01'.format(i) for i in range(1, N+1, 3)], fontsize=16)
plt.gca().xaxis.set_major_formatter(DateFormatter('%Y-%m'))
```
I get the correct result:
![ex4](https://user-images.githubusercontent.com/1224492/34227960-4f0ee348-e5cf-11e7-8db7-6f6172fdb939.png)



#### Problem description

It should be possible to customize the xticks of the result of ``.plot()`` with the standard commands, at least when one accepts to completely discard the standard pandas formatter.

#### Expected Output

More ore less the last one

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

<details>

INSTALLED VERSIONS
------------------
commit: 775099cde4a2424dfb369d79b8b6e2687e5af7f9
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-4-amd64
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8

pandas: 0.22.0.dev0+393.g775099cde
pytest: 3.2.3
pip: 9.0.1
setuptools: 36.7.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.0dev
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.0.0
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.3.0
xlsxwriter: 0.9.6
lxml: 4.1.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1


</details>
