BUG:When SeriesGroupBy.apply to return DataFrame for each group, the result is incorrect
- [x] I have checked that this issue has not already been reported.

- [ ] 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

df = pd.DataFrame(
{
    'name':'a a b b'.split(),
    'n1': [1,20,1,30],
})

def ap_gp(s):
    des = np.where(s>10,'over','not over')
    res = s.to_frame()
    res['des']=des
    return res

df.groupby('name')['n1'].apply(ap_gp)
```

output:
|    |   a | des      |   b |
|---:|----:|:---------|----:|
|  0 |   1 | not over | nan |
|  1 |  20 | over     | nan |
|  2 | nan | not over |   1 |
|  3 | nan | over     |  30 |


#### Expected Output
|    |   n1 | des      |
|---:|-----:|:---------|
|  0 |    1 | not over |
|  1 |   20 | over     |
|  2 |    1 | not over |
|  3 |   30 | over     |


#### Problem description
I think the reason for this error is to modify the name attribute of Series before concat



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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0.post20200210
Cython           : 0.29.15
pytest           : 5.3.5
hypothesis       : 5.5.4
sphinx           : 2.4.0
blosc            : None
feather          : None
xlsxwriter       : 1.2.7
lxml.etree       : 4.5.0
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.12.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : 1.3.2
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.1.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.3.5
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.13
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.7
numba            : 0.48.0
</details>
