-
-
Notifications
You must be signed in to change notification settings - Fork 18.5k
BUG: Unary minus raises for series with Int64Dtype #36063
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Comments
Bisection identified 67aae80 as the first bad commit. (PR #32422) bisect log
setup to reproduce Ran bisection with this shell script, first good/bad commits are 1.0.5 and 1.1.0 releases respectively:
where un.py is import pandas
s = pandas.Series([1, 2, 3], dtype="Int64")
print(-s) |
moving off 1.1.2 milestone, xref #36081 (comment) |
Thanks @kokes cc @jbrockmendel |
Yikes, returning object dtype in the old version is not great. This is just waiting for someone to implement |
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 (commit 73c1d32)
Code Sample, a copy-pastable example
Problem description
I cannot negate series with Int64Dtype. This was possible in previous versions (but it returned object dtype).
Expected Output
Output of
pd.show_versions()
INSTALLED VERSIONS
commit : f2ca0a2
python : 3.8.3.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Thu Jun 18 20:49:00 PDT 2020; root:xnu-6153.141.1~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.1
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 47.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.15.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
The text was updated successfully, but these errors were encountered: