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
from datetime import datetime
import numpy as np
import pandas as pd
years = pd.date_range(start=datetime(1001, 12, 31),
end=datetime(2000, 12, 31),
freq="A", unit="s")
ts = pd.Series(np.arange(1000), index=years)
In [2]: ts.index
Out[2]:
DatetimeIndex(['1001-12-31', '1002-12-31', '1003-12-31', '1004-12-31',
'1005-12-31', '1006-12-31', '1007-12-31', '1008-12-31',
'1009-12-31', '1010-12-31',
...
'1991-12-31', '1992-12-31', '1993-12-31', '1994-12-31',
'1995-12-31', '1996-12-31', '1997-12-31', '1998-12-31',
'1999-12-31', '2000-12-31'],
dtype='datetime64[s]', length=1000, freq='A-DEC')
In [4]: ts.loc["1600"]
---------------------------------------------------------------------------
OutOfBoundsDatetime Traceback (most recent call last)
Cell In[4], line 1
----> 1 ts.loc["1600"]
File ~/miniconda3/envs/Nile-Laki/lib/python3.11/site-packages/pandas/core/indexing.py:1153, in _LocationIndexer.__getitem__(self, key)
1150 axis = self.axis or 0
1152 maybe_callable = com.apply_if_callable(key, self.obj)
-> 1153 return self._getitem_axis(maybe_callable, axis=axis)
File ~/miniconda3/envs/Nile-Laki/lib/python3.11/site-packages/pandas/core/indexing.py:1393, in _LocIndexer._getitem_axis(self, key, axis)
1391 # fall thru to straight lookup
1392 self._validate_key(key, axis)
-> 1393 return self._get_label(key, axis=axis)
File ~/miniconda3/envs/Nile-Laki/lib/python3.11/site-packages/pandas/core/indexing.py:1343, in _LocIndexer._get_label(self, label, axis)
1341 def _get_label(self, label, axis: AxisInt):
1342 # GH#5567 this will fail if the label is not present in the axis.
-> 1343 return self.obj.xs(label, axis=axis)
File ~/miniconda3/envs/Nile-Laki/lib/python3.11/site-packages/pandas/core/generic.py:4236, in NDFrame.xs(self, key, axis, level, drop_level)
4234 new_index = index[loc]
4235 else:
-> 4236 loc = index.get_loc(key)
4238 if isinstance(loc, np.ndarray):
4239 if loc.dtype == np.bool_:
File ~/miniconda3/envs/Nile-Laki/lib/python3.11/site-packages/pandas/core/indexes/datetimes.py:611, in DatetimeIndex.get_loc(self, key)
609 if self._can_partial_date_slice(reso):
610 try:
--> 611 return self._partial_date_slice(reso, parsed)
612 except KeyError as err:
613 raise KeyError(key) from err
File ~/miniconda3/envs/Nile-Laki/lib/python3.11/site-packages/pandas/core/indexes/datetimelike.py:301, in DatetimeIndexOpsMixin._partial_date_slice(self, reso, parsed)
298 if not self._can_partial_date_slice(reso):
299 raise ValueError
--> 301 t1, t2 = self._parsed_string_to_bounds(reso, parsed)
302 vals = self._data._ndarray
303 unbox = self._data._unbox
File ~/miniconda3/envs/Nile-Laki/lib/python3.11/site-packages/pandas/core/indexes/datetimes.py:539, in DatetimeIndex._parsed_string_to_bounds(self, reso, parsed)
524 """
525 Calculate datetime bounds for parsed time string and its resolution.
526
(...)
536 lower, upper: pd.Timestamp
537 """
538 per = Period(parsed, freq=reso.attr_abbrev)
--> 539 start, end = per.start_time, per.end_time
541 # GH 24076
542 # If an incoming date string contained a UTC offset, need to localize
543 # the parsed date to this offset first before aligning with the index's
544 # timezone
545 start = start.tz_localize(parsed.tzinfo)
File period.pyx:1651, in pandas._libs.tslibs.period.PeriodMixin.start_time.__get__()
File period.pyx:2000, in pandas._libs.tslibs.period._Period.to_timestamp()
File period.pyx:1158, in pandas._libs.tslibs.period.period_ordinal_to_dt64()
File np_datetime.pyx:231, in pandas._libs.tslibs.np_datetime.check_dts_bounds()
OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1600-01-01 00:00:00Issue Description
I receive an error trying to index a timeseries with second resolution outside the standard nanosecond range.
It appears that the time series is being converted to nanosecond resolution during the indexing operation.
I believe this is issue would fall under #46587
Expected Behavior
The expected behavior would function as it does within the standard nanosecond range:
In [3]: ts.loc["1700"]
Out[3]:
1700-12-31 699
Freq: A-DEC, dtype: int64
Installed Versions
pandas : 2.1.4
numpy : 1.26.3
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 69.0.3
pip : 23.3.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.1.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.20.0
pandas_datareader : None
bs4 : None
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : 2023.12.2
gcsfs : None
matplotlib : 3.8.2
numba : 0.58.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 14.0.2
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.4
sqlalchemy : None
tables : None
tabulate : None
xarray : 2023.12.0
xlrd : None
zstandard : None
tzdata : 2023.4
qtpy : None
pyqt5 : None