Pandas version checks
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[X] I have checked that this issue has not already been reported.
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[X] I have confirmed this bug exists on the latest version of pandas.
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[X] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
>>> import pandas as pd
>>> pd.Series(["2020-01-01", "2020-02-02"], dtype="datetime64[ns]").astype("datetime64[D]")
0 2020-01-01
1 2020-02-02
dtype: datetime64[ns]
Issue Description
Currently, Pandas does not support non ns resolution datetime types for values. The current behavior is to silently coerce other resolutions to ns. In the case of an explicit cast this leads to quite surprising behavior that is difficult to debug. I discovered this while trying to help someone on stackoverflow who could not get their pandas DataFrame to work with numpy.busday_count.
Expected Behavior
Either cast to the requested resolution of datetime64 or inform the user that the cast was not successful.
Installed Versions
INSTALLED VERSIONS
------------------
commit : 58c124feb4dffe46a73a43fbe995421ea361dfee
python : 3.9.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.102.1-microsoft-standard-WSL2
Version : #1 SMP Wed Mar 2 00:30:59 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.6.0.dev0+75.g58c124feb4
numpy : 1.23.2
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 44.0.0
pip : 20.0.2
Cython : 0.29.32
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None
Comment From: jbrockmendel
This now raises, closing.