to_pickle compression does not work with in-memory buffers
#### Code Sample, a copy-pastable example if possible

```python
from io import BytesIO
import pandas
pandas.DataFrame([[]]).to_pickle(BytesIO(), compression=None)  # works
pandas.DataFrame([[]]).to_pickle(BytesIO())
# ValueError: Unrecognized compression type: infer (regression in 0.24 from 0.23)
pandas.DataFrame([[]]).to_pickle(BytesIO(), compression='zip')
# AttributeError: 'NoneType' object has no attribute 'find' (in 0.24)
# BadZipFile: File is not a zip file (in 0.22 and before)
```
#### Problem description

#22555 is closely related, but I believe this is a different issue because the errors occur at a different place in the code.

I believe the above is an issue because

- Despite the argument name is "path" and the docstring reads `path : string   File path`, the code contains multiple `path_or_buf` names. I'd be happy to make a PR amending the docstring if anybody confirms that the docstring is not precise.
- The code above is actually useful (I want to let the user export a dataframe from a webapp)
- `compression='infer'` failing is a regression

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.1.final.0
python-bits: 64
OS: Linux
OS-release: 5.0.0-13-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.2
pytest: 4.4.1
pip: 19.1
setuptools: 41.0.1
Cython: 0.29.7
numpy: 1.16.3
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.5.0
sphinx: None
patsy: 0.5.1
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.3
openpyxl: None
xlrd: 1.2.0
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: 4.7.1
html5lib: 1.0.1
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
