BUG: to_parquet write partitioned DataFrame to local filesystem for other filesystems (e.g. S3)
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
import pandas as pd

remote = "s3://some-pandas-test-bucket/table"

pd.DataFrame([[1, 'a'], [1, 'b']], columns=['col_one', 'col_two']).to_parquet(remote, partition_cols=['col_two'])
```

#### Problem description

When a DataFrame is to be saved in object file system such as S3 as partitioned Parquet files, it saves the files in local file system instead, only a 0 byte object of is created, whereas the files are stored in the working directory as `s3:`

```
(pandas-dev) ➜  pandas git:(fix/parquet-write-dataset-s3) ✗ ls -R s3:
some-pandas-test-bucket

s3:/some-pandas-test-bucket:
table

s3:/some-pandas-test-bucket/table:
col_two=a col_two=b

s3:/some-pandas-test-bucket/table/col_two=a:
2a386111fd44400b8de1901254a7c485.parquet

s3:/some-pandas-test-bucket/table/col_two=b:
aefb0d5b907a415d943b6bcf59f2521d.parquet
```
On S3
```
(pandas-dev) ➜  pandas git:(fix/parquet-write-dataset-s3) ✗ aws s3 ls s3://some-pandas-test-bucket
2020-06-17 14:44:00          0 table
```

#### Expected Output

```
(pandas-dev) ➜  pandas git:(fix/parquet-write-dataset-s3) ✗ aws s3 ls s3://some-pandas-test-bucket --recursive --human-readable --summarize
2020-06-17 14:46:30    0 Bytes table
2020-06-17 14:46:30    1.3 KiB table/col_two=a/291b3f0d1d1f4eab9d6358e39ac47631.parquet
2020-06-17 14:46:30    1.3 KiB table/col_two=b/834e872441224885a5089554524d3b12.parquet
```

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

<details>


INSTALLED VERSIONS
------------------
commit           : 5fdd6f50ac5ac2de939ef5b849e4c41e27e623a3
python           : 3.8.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.5.0
Version          : Darwin Kernel Version 19.5.0: Tue May 26 20:41:44 PDT 2020; root:xnu-6153.121.2~2/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : None.UTF-8

pandas           : 1.1.0.dev0+1887.g5fdd6f50a.dirty
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.3.1.post20200616
Cython           : 0.29.20
pytest           : 5.4.3
hypothesis       : 5.16.1
sphinx           : 3.1.1
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : 4.5.1
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.15.0
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fastparquet      : 0.4.0
gcsfs            : None
matplotlib       : 3.2.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.4.1
sqlalchemy       : 1.3.17
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.48.0


</details>
