BUG: Incorrect behaviour when using loc
on a resampled time index dataframe
#58255
Open
3 tasks done
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 example above throws a key error.
Interestingly,
df.resample("QS").sum().loc["2015-Q1"]
yields the indices corresponding to the first quarter of 2014.See stackoverflow issue.
https://stackoverflow.com/questions/78315553/pandas-bug-when-trying-to-loc-data-on-a-quarter/78320367?
Expected Behavior
The view should be on the first quarter of 2014. Expected output is
but it doesn't find it. Instead, I get the following with another indexing
Note that the problem disappears if I do
In which case the correct output is yielded.
Installed Versions
INSTALLED VERSIONS
commit : bdc79c1
python : 3.12.2.final.0
python-bits : 64
OS : Darwin
OS-release : 23.4.0
Version : Darwin Kernel Version 23.4.0: Fri Mar 15 00:12:49 PDT 2024; root:xnu-10063.101.17~1/RELEASE_ARM64_T6020
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 2.2.1
numpy : 1.26.4
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
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 : 8.20.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : 1.3.7
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : 2.8.7
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : 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
The text was updated successfully, but these errors were encountered: