Description
Pandas version checks
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I have checked that this issue has not already been reported.
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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
i = pd.date_range('2020-01-01', freq='MS', periods=12)
# DatetimeIndex(['2020-01-01', '2020-02-01', '2020-03-01', '2020-04-01',
# '2020-05-01', '2020-06-01', '2020-07-01', '2020-08-01',
# '2020-09-01', '2020-10-01', '2020-11-01', '2020-12-01'],
# dtype='datetime64[ns]', freq='MS')
# Incorrect result:
i.is_year_start
# array([False, False, False, False, False, False, False, False, False, False, False, True])
# Correct result when first removing the frequency:
i.freq = None
i.is_year_start
# array([True, False, False, False, False, False, False, False, False, False, False, False])
Issue Description
The .freq
property of the DatetimeIndex
influences the result of the .is_year_start
property. If it is set to MonthStart, the december timestamp is incorrectly recognised as the start of the year.
.is_quarter_start
has a similar issue.
The issue does not arise for .freq == 'QS'
.
Expected Behavior
Even if i.freq == 'MS'
, the result of i.is_year_start
should start with True
, not end with True
.
Installed Versions
INSTALLED VERSIONS
commit : 91111fd
python : 3.9.13.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : de_DE.cp1252
pandas : 1.5.1
numpy : 1.23.4
pytz : 2022.6
dateutil : 2.8.2
setuptools : 63.4.1
pip : 22.2.2
Cython : None
pytest : 7.1.3
hypothesis : None
sphinx : 5.3.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.5.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.2
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None