DataFrames don't handle input arrays of dtype str/bytes consistently.

[coady]

Code Sample, a copy-pastable example if possible

In [3]: arr = np.array(['ab', 'bc', 'cd'], bytes)                                                                                                                                                                                               

In [4]: arr.dtype                                                                                                                                                                                                                               
Out[4]: dtype('S2')

In [5]: pd.DataFrame(arr)[0].dtype                                                                                                                                                                                                              
Out[5]: dtype('S2')

In [6]: pd.DataFrame(arr, columns=['x'])['x'].dtype                                                                                                                                                                                             
Out[6]: dtype('S2')

In [7]: pd.DataFrame({'x': arr})['x'].dtype                                                                                                                                                                                                     
Out[7]: dtype('O')

Problem description

DataFrames appear to automatically convert numpy arrays of dtype U to O. But whether they allow columns of dtype S is inconsistent.

Expected Output

Output of pd.show_versions()

[paste the output of pd.show_versions() here below this line]
INSTALLED VERSIONS

commit: None
python: 3.7.1.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.125-linuxkit
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: C.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.4
pytest: None
pip: 18.1
setuptools: 40.6.2
Cython: None
numpy: 1.15.4
scipy: None
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: None
patsy: None
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[chris-b1]

Rolling this under #5261 - in general we don't support numpy string dtypes, but in some construction paths where we try to be zero-copy, they can make it into a DataFrame.

[chris-b1]

(feel free to comment there if you have more specific suggestions)