BUG: pd.Dataframe.sort_values() does not sort values of percentage well.
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

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


### Reproducible Example

```python
import pandas as pd

data1 = {"TIMES": [3, 5, 2, 100, 20]}
df1 = pd.DataFrame(data=data1)
print("===The original dataframe===")
print(df1)

df1["RATIO"] = df1["TIMES"]/df1["TIMES"].sum()
df1["PERCENT"] = df1["RATIO"].apply(lambda x: format(x, ".2%"))
df1 = df1.sort_values(by="RATIO", ascending=True)
print("===The dataframe sort by RATIO===")
print(df1)

df1 = df1.sort_values(by="PERCENT", ascending=True)
print("===The dataframe sort by PERCENT===")
print(df1)
```


### Issue Description

This is what the code out. And when the dataframe is sorted by RATIO , everything is OK .But, when it comes to be sorted by  PERCENT, something is wrong, and the sorted column is not correct as you can see below.

===The original dataframe===
   TIMES
0      3
1      5
2      2
3    100
4     20
===The dataframe sort by RATIO===
   TIMES     RATIO PERCENT
2      2  0.015385   1.54%
0      3  0.023077   2.31%
1      5  0.038462   3.85%
4     20  0.153846  15.38%
3    100  0.769231  76.92%
===The dataframe sort by PERCENT===
   TIMES     RATIO PERCENT
2      2  0.015385   1.54%
4     20  0.153846  15.38%
0      3  0.023077   2.31%
1      5  0.038462   3.85%
3    100  0.769231  76.92%

### Expected Behavior

I expect when the dataframe is sorted by PERCENT, it looks as same as sorted by RATIO.Like this:

===The original dataframe===
   TIMES
0      3
1      5
2      2
3    100
4     20
===The dataframe sort by RATIO===
   TIMES     RATIO PERCENT
2      2  0.015385   1.54%
0      3  0.023077   2.31%
1      5  0.038462   3.85%
4     20  0.153846  15.38%
3    100  0.769231  76.92%
===The dataframe sort by PERCENT===
   TIMES     RATIO PERCENT
2      2  0.015385   1.54%
0      3  0.023077   2.31%
1      5  0.038462   3.85%
4     20  0.153846  15.38%
3    100  0.769231  76.92%

### Installed Versions

<details>
INSTALLED VERSIONS
------------------
commit           : 73c68257545b5f8530b7044f56647bd2db92e2ba
python           : 3.8.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.4.0-19041-Microsoft
Version          : #1237-Microsoft Sat Sep 11 14:32:00 PST 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.3
numpy            : 1.21.1
pytz             : 2021.1
dateutil         : 2.8.2
pip              : 20.0.2
setuptools       : 45.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.1
IPython          : None
pandas_datareader: None
bs4              : 4.10.0
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None
</details>
