BUG: clip does not accept numpy's arguments
- [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.

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

---

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

```python
x = pd.Series(np.random.randn(100))
x.clip(lower=0)         # Works
x.clip(lower=0, min=0)  # TypeError: clip() got an unexpected keyword argument 'min'
```

#### Problem description

Documentation of `clip` ([dataframe](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.clip.html), [series](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.clip.html)) states the method signature:
```python
Series.clip(self: ~ FrameOrSeries, lower=None, upper=None, axis=None, inplace: bool = False, *args, **kwargs)
```
and explains about `**kwargs`:
```
*args, **kwargs
Additional keywords have no effect but might be accepted for compatibility with numpy.
```

However `min` or `max` arguments of numpy are not accepted and raised `TypeError`.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.1.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.5
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 42.0.1.post20191125
Cython           : None
pytest           : 5.3.0
hypothesis       : None
sphinx           : 2.2.0
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.4.1
html5lib         : None
pymysql          : 0.9.3
psycopg2         : 2.8.5 (dt dec pq3 ext lo64)
jinja2           : 2.10.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.6.3
bottleneck       : None
fastparquet      : 0.3.2
gcsfs            : None
lxml.etree       : 4.4.1
matplotlib       : 3.1.3
numexpr          : 2.7.0
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pytest           : 5.3.0
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.5.1
sqlalchemy       : 1.3.13
tables           : 3.4.4
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.1.0
xlwt             : None
xlsxwriter       : None
numba            : 0.46.0
</details>
