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I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
(optional) I have confirmed this bug exists on the master branch of pandas.
>>> import pandas as pd >>> sr = pd.Series([10, 20, 30], dtype='timedelta64[ns]') >>> sr 0 00:00:00.000000 1 00:00:00.000000 2 00:00:00.000000 dtype: timedelta64[ns] >>> sr = pd.Series([1000, 20, 30], dtype='timedelta64[ns]') >>> sr 0 00:00:00.000001 1 00:00:00.000000 2 00:00:00.000000 dtype: timedelta64[ns] >>> sr = pd.Series([1000, 222330, 30], dtype='timedelta64[ns]') >>> sr 0 00:00:00.000001 1 00:00:00.000222 2 00:00:00.000000 dtype: timedelta64[ns] >>> sr1 = pd.Series([1000, 222330, None], dtype='timedelta64[ns]') >>> sr1 0 00:00:00.000001 1 00:00:00.000222 2 NaT dtype: timedelta64[ns] >>> sr / sr1 0 1.0 1 1.0 2 NaN dtype: float64 >>> sr // sr1 Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/nvme/0/pgali/envs/cudfdev1/lib/python3.7/site-packages/pandas/core/ops/common.py", line 64, in new_method return method(self, other) File "/nvme/0/pgali/envs/cudfdev1/lib/python3.7/site-packages/pandas/core/ops/__init__.py", line 503, in wrapper result = arithmetic_op(lvalues, rvalues, op, str_rep) File "/nvme/0/pgali/envs/cudfdev1/lib/python3.7/site-packages/pandas/core/ops/array_ops.py", line 193, in arithmetic_op res_values = dispatch_to_extension_op(op, lvalues, rvalues) File "/nvme/0/pgali/envs/cudfdev1/lib/python3.7/site-packages/pandas/core/ops/dispatch.py", line 125, in dispatch_to_extension_op res_values = op(left, right) File "/nvme/0/pgali/envs/cudfdev1/lib/python3.7/site-packages/pandas/core/arrays/timedeltas.py", line 637, in __floordiv__ result[mask] = np.nan ValueError: cannot convert float NaN to integer
When there is a NaT in either of the series, the result should ideally be of type nullable integer (Int64) to avoid this kind of ValueError
NaT
nullable
Int64
ValueError
pd.show_versions()
commit : None python : 3.7.6.final.0 python-bits : 64 OS : Linux OS-release : 4.15.0-76-generic machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8
pandas : 1.0.5 numpy : 1.18.5 pytz : 2020.1 dateutil : 2.8.1 pip : 20.1.1 setuptools : 49.1.0.post20200704 Cython : 0.29.21 pytest : 5.4.3 hypothesis : 5.19.0 sphinx : 3.1.2 blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 2.11.2 IPython : 7.16.1 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 : 0.17.1 pytables : None pytest : 5.4.3 pyxlsb : None s3fs : None scipy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlwt : None xlsxwriter : None numba : 0.50.1
The text was updated successfully, but these errors were encountered:
Remove xfails related to pandas-dev/pandas#35529
5af7e63
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I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
(optional) I have confirmed this bug exists on the master branch of pandas.
Code Sample, a copy-pastable example
Problem description
When there is a
NaT
in either of the series, the result should ideally be of typenullable
integer (Int64
) to avoid this kind ofValueError
Expected Output
Output of
pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.7.6.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-76-generic
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.0.5
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.1.0.post20200704
Cython : 0.29.21
pytest : 5.4.3
hypothesis : 5.19.0
sphinx : 3.1.2
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
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 : 0.17.1
pytables : None
pytest : 5.4.3
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : 0.50.1
The text was updated successfully, but these errors were encountered: