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ipdb> value = np.array([np.datetime64(1, 'ms')], dtype="<M8[ms]") ipdb> pd.Series(value) 0 1970-01-01 00:00:00.001 dtype: datetime64[ns] ipdb> value = np.array([np.datetime64(1, 'ms')], dtype=">M8[ms]") ipdb> pd.Series(value) *** pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 2285384-04-02 23:52:07
Seems like something weird is going on when converting the big-endian timestamp, which does not happen for the little-endian one.
The same as for the little-endian data type.
pd.show_versions()
[paste the output of pd.show_versions() here below this line]
ipdb> pd.show_versions()
commit : None python : 3.7.3.final.0 python-bits : 64 OS : Darwin OS-release : 18.5.0 machine : x86_64 processor : i386 byteorder : little LC_ALL : en_US.UTF-8 LANG : en_US.UTF-8 LOCALE : en_US.UTF-8
pandas : 0.25.3 numpy : 1.17.3 pytz : 2019.3 dateutil : 2.8.1 pip : 19.3.1 setuptools : 41.6.0.post20191101 Cython : None pytest : 5.0.1 hypothesis : 4.44.2 sphinx : 2.2.1 blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 2.10.3 IPython : 7.9.0 pandas_datareader: None bs4 : None bottleneck : None fastparquet : None gcsfs : None lxml.etree : None matplotlib : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 0.13.0 pytables : None s3fs : None scipy : None sqlalchemy : None tables : None xarray : None xlrd : None xlwt : None xlsxwriter : None
The text was updated successfully, but these errors were encountered:
This doesn't affect pandas 0.24.2. With that version, it works as expected
0.24.2
Sorry, something went wrong.
@lr4d Thanks for the report, I can confirm this is a regression compared to pandas 0.24.
@jbrockmendel do you know if we have / had special handling for this in the tslib code?
I'm not aware of anything endian-specific in the tslibs code. I'll try to take a look at this
jbrockmendel
Successfully merging a pull request may close this issue.
Code Sample, a copy-pastable example if possible
Problem description
Seems like something weird is going on when converting the big-endian timestamp, which does not happen for the little-endian one.
Expected Output
The same as for the little-endian data type.
Output of
pd.show_versions()
[paste the output of
pd.show_versions()
here below this line]ipdb> pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.7.3.final.0
python-bits : 64
OS : Darwin
OS-release : 18.5.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.25.3
numpy : 1.17.3
pytz : 2019.3
dateutil : 2.8.1
pip : 19.3.1
setuptools : 41.6.0.post20191101
Cython : None
pytest : 5.0.1
hypothesis : 4.44.2
sphinx : 2.2.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.13.0
pytables : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
The text was updated successfully, but these errors were encountered: