Pandas version checks
Reproducible Example
import pandas as pd
import datetime as dt
df = pd.DataFrame([{'id': 1},{'id': 2},{'id': 3}])
_time = dt.datetime.utcfromtimestamp(1695887042)
_time = _time.replace(tzinfo=dt.timezone.utc)
df.loc[df.id>=2, 'time'] = _time
print(df)
print(df.dtypes)Issue Description
the above outputs
id time
0 1 NaT
1 2 2023-09-28 07:44:02+00:00
2 3 2023-09-28 07:44:02+00:00
id int64
time object
dtype: object
Expected Behavior
it would be nice to get to
id time
0 1 NaT
1 2 2023-09-28 07:44:02+00:00
2 3 2023-09-28 07:44:02+00:00
id int64
time datetime64[ns, UTC]
dtype: object
right away
Installed Versions
Details
[1/1] Generating write_version_file with a custom command
- /home/marcogorelli/.virtualenvs/pandas/bin/ninja
INSTALLED VERSIONS
commit : 99efe62
python : 3.10.12.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 : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 2.1.0rc0+99.g99efe62afd.dirty
numpy : 1.24.4
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 59.6.0
pip : 23.2.1
Cython : 0.29.33
pytest : 7.4.2
hypothesis : 6.86.2
sphinx : 6.2.1
blosc : 1.11.1
feather : None
xlsxwriter : 3.1.4
lxml.etree : 4.9.3
html5lib : 1.1
pymysql : 1.4.6
psycopg2 : 2.9.7
jinja2 : 3.1.2
IPython : 8.15.0
pandas_datareader : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat: None
fastparquet : 2023.8.0
fsspec : 2023.9.1
gcsfs : 2023.9.1
matplotlib : 3.7.3
numba : 0.57.1
numexpr : 2.8.6
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 13.0.0
pyreadstat : 1.2.3
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2023.9.1
scipy : 1.11.2
sqlalchemy : 2.0.21
tables : 3.8.0
tabulate : 0.9.0
xarray : 2023.8.0
xlrd : 2.0.1
zstandard : 0.21.0
tzdata : 2023.3
qtpy : None
pyqt5 : None
None
Pandas version checks
I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
Issue Description
the above outputs
Expected Behavior
it would be nice to get to
right away
Installed Versions
Details
[1/1] Generating write_version_file with a custom command
INSTALLED VERSIONS
commit : 99efe62
python : 3.10.12.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 : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 2.1.0rc0+99.g99efe62afd.dirty
numpy : 1.24.4
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 59.6.0
pip : 23.2.1
Cython : 0.29.33
pytest : 7.4.2
hypothesis : 6.86.2
sphinx : 6.2.1
blosc : 1.11.1
feather : None
xlsxwriter : 3.1.4
lxml.etree : 4.9.3
html5lib : 1.1
pymysql : 1.4.6
psycopg2 : 2.9.7
jinja2 : 3.1.2
IPython : 8.15.0
pandas_datareader : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat: None
fastparquet : 2023.8.0
fsspec : 2023.9.1
gcsfs : 2023.9.1
matplotlib : 3.7.3
numba : 0.57.1
numexpr : 2.8.6
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 13.0.0
pyreadstat : 1.2.3
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2023.9.1
scipy : 1.11.2
sqlalchemy : 2.0.21
tables : 3.8.0
tabulate : 0.9.0
xarray : 2023.8.0
xlrd : 2.0.1
zstandard : 0.21.0
tzdata : 2023.3
qtpy : None
pyqt5 : None
None