DataFrame.values sometimes returns a view and sometimes a copy
Example 1 (`.values` returning a view)

```python
df = pd.DataFrame([["A", "B"],["C", "D"]])

df.values[0][0] = 0

df.values[0][1] = 5
# df
#     0   1
# 0   0   5
# 1   C   D
```
Example 2 (`.values` returning a copy) (Taken from COLDSPEED's answer in [this question](https://stackoverflow.com/questions/48201521/will-changes-in-dataframe-values-always-modify-the-values-in-the-data-frame))

```python
In [755]: df = pd.DataFrame({'A' :[1, 2], 'B' : ['ccc', 'ddd']})

In [756]: df
Out[756]: 
   A    B
0  1  ccc
1  2  ddd

In [757]: v = df.values

In [758]: v[0] = 123

In [759]: v[0, 1] = 'zzxxx'

In [760]: df
Out[760]: 
   A    B
0  1  ccc
1  2  ddd
```

#### Problem description

This is based on a question I asked on SO, [Will changes in DataFrame.values always modify the values in the data frame?](https://stackoverflow.com/questions/48201521/will-changes-in-dataframe-values-always-modify-the-values-in-the-data-frame). You can see from the two examples above, sometimes, `.values` function returns a view while sometimes returns a copy. 

I wonder whether this is safe. 

I would advocate adding an option to force returning a view or copy. This is because someone can do some process on `df.values` and change `df` by accident. Or when people expect to change the values on a df but it does not happen because a copy is returned. See this [question](https://stackoverflow.com/questions/24475094/set-values-on-the-diagonal-of-pandas-dataframe) for example. People are advocating changing `df.values` directly like `np.fill_diagonal(df.values, 0)` to change the diagonal part of a data frame. 

 I think users at least need to be warned. Now on the documentation, it only contains a line ["Numpy representation of NDFrame"](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.values.html) 

#### Expected Output

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

<details>

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

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: 3.2.1
pip: 9.0.1
setuptools: 36.5.0.post20170921
Cython: 0.26.1
numpy: 1.14.0
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.1.0
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.2.0
xlsxwriter: 1.0.2
lxml: 4.1.0
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
