BUG: Inconsistent behavior of index values for `DataFrame.apply` and `Series.apply`
- [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.

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**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
pdf = pd.DataFrame([[4, 9]] * 3, columns=['A', 'B'])
pdf.apply(["sum", lambda df: df.sum(), lambda df: df.sum()]) # lambdas have postfix 0, 1 ...
             A   B
sum         12  27
<lambda_0>  12  27
<lambda_1>  12  27
s = pd.Series([4] * 3)
s.apply(["sum", lambda df: df.sum(), lambda df: df.sum()]) # lambdas have not postfix 0, 1 ...
sum         12
<lambda>    12
<lambda>    12
dtype: int64
```

#### Problem description

Could anyone explain please? Is it normal behavior? Why DataFrame's index has postfix for lambdas, but Series's index hasn't. The same behavior is observed for `agg`. There is no such behavior in pandas==1.0.5.

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

<details>

pandas : 1.1.1
numpy : 1.18.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 41.2.0
Cython : None
pytest : 5.4.2
hypothesis : None
sphinx : None
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.14.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : 0.7.3
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.4.1
sqlalchemy : 1.3.17
tables : 3.6.1
tabulate : None
xarray : 0.15.1
xlrd : 1.2.0
xlwt : None
numba : None

</details>
