BUG: attrs lost for Series in DataFrame
- [x] I have checked that this issue has not already been reported.
  - Has sort of come up in other issues related to metadata/attrs not propagating through properly, however I haven't seen any issues specifically about `Series` attrs being lost when put into a `DataFrame`.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (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

See this [GitHub Gist Notebook](https://gist.github.com/RobertRosca/d3c53151dd93242c448daf008fb4bb23).

Summary of the issue is:

```python
import pandas as pd

#  Make some dummy dataframe
df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})

#  Make some dummy series
col1_w_attr = df["col1"].copy()
#  Add some attrs to it
col1_w_attr.attrs["test_attr"] = 1
df["col1_w_attr"] = col1_w_attr
#  Issue 1: The attrs are missing, call `__finalize__` manually
df["col1_w_attr"].__finalize__(col1_w_attr)

#  Repeat the above with another column:
col2_w_attr = df["col2"].copy()
col2_w_attr.attrs["test_attr"] = 2
df["col2_w_attr"] = col2_w_attr
df["col2_w_attr"].__finalize__(col2_w_attr)

#  Attrs are present as before
df["col2_w_attr"].attrs

#  Issue 2: col1_w_attrs is now missing its attrs:
df["col1_w_attr"].attrs
```

#### Problem description

First issue is that attrs are not propagated through when a `Series` is added to a `DataFrame` (likely related to #28283).

Second issue is that if you call `__finalize__` to make sure that the attrs are present, once you add another column in or modify the dataframe, the attrs already present for a column are lost. My guess is that when the DataFrame is modified, finalize is not called per-column again, but I haven't looked into it much.

I'd be happy to help with this issue, however there are already many issues related to this topic and a few branches where others are working on attrs/metadata/finalize, so I'm a bit hesitant to start work as it'll probably conflict with what has already been done.

What would be the best place to discuss collaboration on this?

#### Expected Output

Expectation would be that you can attach some attrs to a Series, place it into a dataframe, modify/work with the dataframe, then access the attrs again.

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

<details>

import pandas as pd

pd.show_versions()


INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.3.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.7.0-3-MANJARO
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : en_GB.UTF-8
LOCALE           : en_GB.UTF-8

pandas           : 1.0.5
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 19.2.3
setuptools       : 41.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
