Enhancement:  to_json and read_json for DataFrame should have option to output/parse values by column
#### Code Sample, a copy-pastable example if possible

```python
ll = [(1, "a", 4), (2, "b", 5), (3, "c", 6)]
df = pd.DataFrame(ll, columns=["one", "two", "three"])
print(df.to_json(orient='split'))
print(df['one'].to_json(orient='split'))
```
#### Problem description

The output for this code is:
```
{"columns":["one","two","three"],"index":[0,1,2],"data":[[1,"a",4],[2,"b",5],[3,"c",6]]}
{"name":"one","index":[0,1,2],"data":[1,2,3]}
```
Note that the values for the `DataFrame` are _by row_, whereas the values for the `Series` are _by column_.

The issue with the `DataFrame` version is that parsing the values in a type-safe language requires you to handle each element of the array as a different type, while using the Series format, the values are all of one type.

So I'd like to propose that we add an `orient='columns'` for `DataFrame`.  In this case, it would look just like the `'split'` option, but instead of a `'data'` field, it would have a `'cdata'` field, where you'd have a list of values for each column of the DataFrame. 

Note that this can almost be done by using `df.T.to_json(orient='split')`, but that reverses the meaning of `'index'` and `'columns'` in the resulting JSON.

Finally, I presume we'd want to change the implementation of `read_json()` and `to_json()`.

#### Expected Output
```python
print(df.to_json(orient='columns''))
```
would produce
```
{"columns":["one","two","three"],"index":[0,1,2],"cdata":[[1,2,3],["a","b","c"],[4,5,6]]}
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.20.3
pytest: None
pip: 9.0.1
setuptools: 27.2.0
Cython: None
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 6.0.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.0
openpyxl: None
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
