Pandas version checks

  • [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.

  • [X] I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

[ins] In [3]: pd.DataFrame({"a": np.array([b'abc'], dtype="S3")}).iloc[:, 0].dtype
Out[3]: dtype('O')

[ins] In [4]: foo = pd.DataFrame(); foo['a'] = np.array([b'abc'], dtype="S3"); foo['a'].dtype
Out[4]: dtype('S3')

Issue Description

The same numpy should have the same dtypes when turned into a pandas series through different approaches, but they are differnt. The 'S3' dtype is harder to deal with because things like df.select_dtype(object) don't work.

Expected Behavior

The best case is that both should be object dtype. Barring that, having them be the same dtype would be nice.

Installed Versions

I apologize that I can't test this in the newest version -- my organization has not upgraded yet: 
INSTALLED VERSIONS
------------------
commit           : 66e3805b8cabe977f40c05259cc3fcf7ead5687d
python           : 3.8.13.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.18.0-348.23.1.el8_5.x86_64
Version          : #1 SMP Tue Apr 12 11:20:32 EDT 2022
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.5
numpy            : 1.23.3
pytz             : 2022.4
dateutil         : 2.8.2
pip              : 22.2.2
setuptools       : 65.4.1
Cython           : 0.29.32
pytest           : 7.0.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.8.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.1.2
IPython          : 8.5.0
pandas_datareader: None
bs4              : 4.11.1
bottleneck       : 1.3.5
fsspec           : 2022.8.2
fastparquet      : None
gcsfs            : None
matplotlib       : 3.6.0
numexpr          : 2.8.3
odfpy            : None
openpyxl         : 3.0.10
pandas_gbq       : None
pyarrow          : 9.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.9.1
sqlalchemy       : 1.4.41
tables           : 3.6.1
tabulate         : 0.9.0
xarray           : 2022.9.0
xlrd             : 2.0.1
xlwt             : None
numba            : 0.56.2

Comment From: phofl

Hi, thanks for your report. We should never end up with S3 or similar, but this is a know issue. Could you double check the issue tracker?

Comment From: zbs

I searched for is:issue series bytes dtype and is:issue series s dtype, but couldn't find anything.