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BUG: Rolling pd.date_range incorrect for unit='s'
#55026
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@jorisvandenbossche I can try to find the issue here :) |
Thanks @hkhojasteh, really appreciate your effort on this. |
Welcome! Hopefully you will have the fixes in the next release soon :) |
…conds (#55173) * Fix rolling microseconds for sum * - adding a test for rounding sum * Update pandas/tests/window/test_rolling.py Co-authored-by: Joris Van den Bossche <[email protected]> * Update test_rolling.py the df variable name fixed in the test * Reverted version varialbe in doc/source/conf.py * Units generalised to us/ms/s and test parameterised * Rolling max tests added, related to #55026 * whatsnew note for 2.1.2 added * Update doc/source/whatsnew/v2.1.2.rst Co-authored-by: Matthew Roeschke <[email protected]> * UTC timezone for _index_array of rolling * Validating tz-aware data Data conversion removed Tests merged * Conversion replaced by Timedelta.as_unit * fixes for failing tests * update whatsnew * type checking --------- Co-authored-by: Joris Van den Bossche <[email protected]> Co-authored-by: Matthew Roeschke <[email protected]>
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Reproducible Example
Issue Description
Hi,
We've noticed that a
pd.date_range
withunit='s'
gives incorrect results when we apply arolling
function. It appears to return theexpanding
result rather thanrolling
.Expected Behavior
The expected result is the same as for
unit='ns'
in the above snippet, I.e. a max of 1 for the first 4 days and 0 beyond that.Installed Versions
INSTALLED VERSIONS
commit : ba1cccd
python : 3.11.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 94 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252
pandas : 2.1.0
numpy : 1.25.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.1.2
pip : 23.2.1
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 : 8.15.0
pandas_datareader : None
bs4 : None
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.7.2
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None
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