Description
Code Sample
import pandas as pd
pd.__version__
# df created from list, None is casted to str
df = pd.DataFrame(["1", "2", None], columns=["a"], dtype="str")
type(df.loc[2].values[0])
# Equivalent df created from dict, None remains NoneType
df = pd.DataFrame({"a": ["1", "2", None]}, dtype="str")
type(df.loc[2].values[0]))Problem description
None is not casted consistently for DataFrames with None values and dtype set to str.
If DataFrame is created from list, then None is casted to str -> None -> "None".
If DataFrame is created from dict, then None remains NoneType -> None -> None.
IMO, the latter is the preferred behavior. I hope you consider this when continuing your work on string types and na types in future versions.
Expected Output
Output of pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.7.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, 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 : 41.2.0
Cython : None
pytest : 5.3.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.12.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pytest : 5.3.5
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : None