BUG: DatetimeIndex.is_year_start breaks on custom business days frequencies bigger then 1C · Issue #58664 · pandas-dev/pandas (original) (raw)

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

import pandas as pd

dr1 = pd.date_range("2020-01-01", periods=1, freq="2C") print(dr1.is_year_start)

dr2 = pd.date_range("2020-01-01", periods=1, freq="C") print(dr2.is_year_start)

Issue Description

This outputs:

[ True]
........
ValueError: Custom business days is not supported by is_year_start

Expected Behavior

it should raise ValueError in both cases

ValueError: Custom business days is not supported by is_year_start

Installed Versions

commit : ae1928b
python : 3.10.13.final.0
python-bits : 64
OS : Linux
OS-release : 4.19.0-22-amd64
Version : #1 SMP Debian 4.19.260-1 (2022-09-29)
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 3.0.0.dev0+478.gae1928b0aa.dirty
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0
setuptools : 69.1.1
pip : 24.0
Cython : 3.0.8
pytest : 8.0.2
hypothesis : 6.98.17
sphinx : 7.2.6
blosc : None
feather : None
xlsxwriter : 3.1.9
lxml.etree : 5.1.0
html5lib : 1.1
pymysql : 1.4.6
psycopg2 : 2.9.9
jinja2 : 3.1.3
IPython : 8.22.2
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : 1.3.8
fastparquet : 2024.2.0
fsspec : 2024.2.0
gcsfs : 2024.2.0
matplotlib : 3.8.3
numba : 0.59.0
numexpr : 2.9.0
odfpy : None
openpyxl : 3.1.2
pyarrow : 15.0.0
pyreadstat : 1.2.6
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2024.2.0
scipy : 1.12.0
sqlalchemy : 2.0.27
tables : 3.9.2
tabulate : 0.9.0
xarray : 2024.2.0
xlrd : 2.0.1
zstandard : 0.22.0
tzdata : 2024.1
qtpy : None
pyqt5 : None