to_csv() with a single level row MultiIndex does not produce the desired output
#### Code Sample, a copy-pastable example if possible

```python
>>> import pandas as pd; 
>>> idx_1d = pd.MultiIndex(levels=[[1.0]], labels=[[0]], names=['x'])
>>> idx_2d = pd.MultiIndex(levels=[[1.], [2.]], labels=[[0], [0]], names=['x', 'y'])

# DataFrame
>>> print(pd.DataFrame({'data': [1]}, idx_2d).to_csv())
x,y,data
1.0,2.0,1

>>> print(pd.DataFrame({'data': [1]}, idx_1d).to_csv())
x,data
"('1.0',)",1

# Series
>>> print(pd.Series([1], idx_2d).to_csv())
1.0,2.0,1

>>> print(pd.Series([1], idx_1d).to_csv())
"('1.0',)",1

```
#### Problem description
The output for `index.nlevels==1` should be the same as for `index.nlevels==2`, with one column less. That matches the output from other index types and was the output produced by pandas up to 0.20.3.

#### Expected Output
```python
>>> print(pd.DataFrame({'data': [1]}, idx_1d).to_csv())
x,data
1.0,1

>>> print(pd.Series([1], idx_1d).to_csv())
1.0,1
```
#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0
pytest: 3.2.1
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.11.3
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 5.1.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.0
tables: 3.4.2
numexpr: 2.6.1
feather: None
matplotlib: 2.0.0
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 4.1.1
bs4: 4.5.3
html5lib: None
sqlalchemy: 1.1.5
pymysql: None
psycopg2: None
jinja2: 2.9.4
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
