BUG: Clipping a data frame after selecting only numeric columns does not work
- [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.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

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

```python
import pandas as pd
import numpy as np

df1 = pd.DataFrame({'A': [100] * 10, 'B': [100] * 10, 'C': ['abc'] * 10})
df1.loc[:, df1.select_dtypes(include=[np.number]).columns].clip(-90, 90, inplace=True)

```

#### Problem description
I am trying to clip the values of all numeric columns in the dataframe.

Initially, the data frame is 
```
	A	B	C
0	100	100	abc
1	100	100	abc
2	100	100	abc
3	100	100	abc
4	100	100	abc
5	100	100	abc
6	100	100	abc
7	100	100	abc
8	100	100	abc
9	100	100	abc
```
The numeric columns are A and B, so
`df1.loc[:, df1.select_dtypes(include=[np.number]).columns]` selects the required columns.

`df1.loc[:, df1.select_dtypes(include=[np.number]).columns].clip(-90, 90, inplace=True)` should clip values in A and B to 90.

Dataframe after clipping is:
```
	A	B	C
0	100	100	abc
1	100	100	abc
2	100	100	abc
3	100	100	abc
4	100	100	abc
5	100	100	abc
6	100	100	abc
7	100	100	abc
8	100	100	abc
9	100	100	abc
```
Clearly, the values are not getting clipped.

#### Expected Output
```
	A	B	C
0	90	90	abc
1	90	90	abc
2	90	90	abc
3	90	90	abc
4	90	90	abc
5	90	90	abc
6	90	90	abc
7	90	90	abc
8	90	90	abc
9	90	90	abc
```
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None

pandas           : 1.0.3
numpy            : 1.17.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 19.2.3
setuptools       : 41.4.0
Cython           : 0.29.13
pytest           : 5.2.1
hypothesis       : None
sphinx           : 2.4.4
blosc            : None
feather          : None
xlsxwriter       : 1.2.1
lxml.etree       : 4.4.1
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.8.4 (dt dec pq3 ext lo64)
jinja2           : 2.10.3
IPython          : 7.8.0
pandas_datareader: None
bs4              : 4.8.0
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.4.1
matplotlib       : 3.1.1
numexpr          : 2.7.0
odfpy            : None
openpyxl         : 3.0.0
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.2.1
pyxlsb           : None
s3fs             : None
scipy            : 1.3.1
sqlalchemy       : 1.3.15
tables           : 3.5.2
tabulate         : 0.8.6
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.1
numba            : 0.45.1

</details>
