Use expanduser when writing dataframes to files?
#### Code Sample, a copy-pastable example if possible

The following `to_XXX` do not work:
```python
df = pd.DataFrame([[1,1],[2,2]])
df.to_pickle('~/df.pkl')
df.to_json('~/df.json')
 # etc.

```
#### Problem description

`to_XXX` do not work when the path argument includes a `~`.  This may be fine, but it is strange that dataframe *reading* from files does support `~`.    i.e. `pd.read_json('~/df.json')` works fine.



#### Expected Output
I expect `to_json` and friends to support expanding the home directory.

Perhaps the fix is to add `expanduser` to https://github.com/pandas-dev/pandas/blob/0d6cb3c21d1305d75878eee7a470bf463b6754bd/pandas/io/common.py#L121
as we have in https://github.com/pandas-dev/pandas/blob/0d6cb3c21d1305d75878eee7a470bf463b6754bd/pandas/io/common.py#L229

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Darwin
OS-release: 17.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.4
pytest: 3.9.1
pip: 9.0.1
setuptools: 40.4.1
Cython: 0.27.3
numpy: 1.15.2
scipy: 1.1.0
pyarrow: 0.10.0
xarray: None
IPython: 5.3.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
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: 0.9999999
sqlalchemy: 1.1.15
pymysql: None
psycopg2: 2.7.1 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: 0.1.5
fastparquet: 0.1.3
pandas_gbq: None
pandas_datareader: None

</details>
