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.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
>>> import pandas as pd
>>> i = pd.date_range('2020-02-01', freq='QS-MAY', periods=3)
>>> i
DatetimeIndex(['2020-02-01', '2020-05-01', '2020-08-01'], dtype='datetime64[ns]', freq='QS-MAY')
>>> pd.DatetimeIndex(i, freq='QS-FEB')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Program Files\Python312\Lib\site-packages\pandas\core\indexes\datetimes.py", line 370, in __new__
dtarr = DatetimeArray._from_sequence_not_strict(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Program Files\Python312\Lib\site-packages\pandas\core\arrays\datetimes.py", line 394, in _from_sequence_not_strict
result._maybe_pin_freq(freq, validate_kwds)
File "C:\Program Files\Python312\Lib\site-packages\pandas\core\arrays\datetimelike.py", line 2094, in _maybe_pin_freq
_validate_inferred_freq(freq, self._freq)
File "C:\Program Files\Python312\Lib\site-packages\pandas\core\arrays\datetimelike.py", line 2526, in _validate_inferred_freq
raise ValueError(
ValueError: Inferred frequency <QuarterBegin: startingMonth=5> from passed values does not conform to passed frequency QS-FEBIssue Description
pd.DatetimeIndex(...), when passed both an index with a frequency, AND a frequency, throws an error if the frequencies are unequal - even if they are equivalent.
Expected Behavior
If the frequencies are unequal, but equivalent (like in the example), an index with the specified (new) frequency should be returned.
That the frequencies are equivalent can be seen in the following snippet: simply direct setting the frequency of i to the specified frequency DOES work:
>>> i = pd.date_range('2020-02-01', freq='QS-MAY', periods=3)
>>> i.freq = 'QS-FEB'
>>> i
DatetimeIndex(['2020-02-01', '2020-05-01', '2020-08-01'], dtype='datetime64[ns]', freq='QS-FEB')
I think this only occurs for quarter-frequency, where "equivalent" means that the starting month mod 3 is equal.
Current workaround:
We don't want to change i, so the current workaround to i2 = pd.DatetimeIndex(i, freq='QS-FEB') is
i2 = i.copy()
i2.freq = 'QS-FEB'
...which is cumbersome, because it requires 2 steps and cannot be used in list comprehensions etc.
Alternatively, there is the elegant
i2 = pd.DatetimeIndex(i, freq=None).to_frame().asfreq(i.freq).index
Installed Versions
pandas : 2.2.3
numpy : 2.1.1
pytz : 2024.2
dateutil : 2.9.0.post0
pip : 24.2
Cython : None
sphinx : None
IPython : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : None
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2024.2
qtpy : None
pyqt5 : None