TimeStamp column name to_csv date_format
Hi, I am new to github and this is my first post so sry for the layout.

#### Code
```python
import pandas as pd

date_parser = "%Y-%m-%d"
d = {'2019-07-09': [1, 2]}
df = pd.DataFrame(data=d)
df.columns = pd.to_datetime(df.columns, format=date_parser)
print(df)
df['second_column'] = df[df.columns]
print(df)
df.to_csv("test.csv", header=True, index=True, date_format=date_parser)
```
#### Problem description
I tried to export dataframe to csv using DataFrame to_csv() with column name as TimeStamp format, but date_format doesn't seem to work on column name, so I get 2019-07-09 00:00:00 instead of 2019-07-09 in my csv file.
By the way, I don't understand why before df['second_column'] = df[df.columns], my first column name format is 2019-07-09, and after this line is 2019-07-09 00:00:00. 

#### output
```   
2019-07-09
0           1
1           2
   2019-07-09 00:00:00  second_column
0                    1              1
1                    2              2
```
#### test.csv
```
,2019-07-09 00:00:00,second_column
0,1,1
1,2,2
```
#### Expected test.csv
```
,2019-07-09,second_column
0,1,1
1,2,2
```
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.8.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-54-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: fr_FR.UTF-8
LOCALE: fr_FR.UTF-8

pandas: 0.24.2
pytest: None
pip: 9.0.1
setuptools: 41.0.1
Cython: None
numpy: 1.16.4
scipy: 1.3.0
pyarrow: None
xarray: None
IPython: 5.5.0
sphinx: 1.6.7
patsy: None
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.1.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: 0.9.6
lxml.etree: 4.2.1
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
<details>

[paste the output of ``pd.show_versions()`` here below this line]

</details>
