Pandas version checks
Reproducible Example
import pandas as pd
import numpy as np
import timeit
n = 1_000_000
df = pd.DataFrame({"a": np.random.randn(n)})
df.index.name = "idx"
runs = 20
t1 = timeit.timeit(lambda: df.sort_index(), number=runs) / runs * 1000
t2 = timeit.timeit(lambda: df.sort_index(level="idx"), number=runs) / runs * 1000
print(f"pandas version: {pd.version}")
print(f"sort_index() : {t1:.2f} ms")
print(f"sort_index(level='idx') : {t2:.2f} ms")
print(f"overhead ratio : {t2 / t1:.1f}x")
Installed Versions
Details
INSTALLED VERSIONS
commit : aac1998
python : 3.13.7
python-bits : 64
OS : Darwin
OS-release : 24.6.0
Version : Darwin Kernel Version 24.6.0: Wed Nov 5 21:32:38 PST 2025; root:xnu-11417.140.69.705.2~1/RELEASE_ARM64_T6031
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0+untagged.3.gaac1998.dirty
numpy : 2.4.2
dateutil : 2.9.0.post0
pip : 25.2
Cython : 3.2.4
sphinx : None
IPython : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : 6.151.9
gcsfs : None
jinja2 : None
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
psycopg2 : None
pymysql : None
pyarrow : 23.0.1
pyiceberg : None
pyreadstat : None
pytest : 9.0.2
python-calamine : None
pytz : 2026.1.post1
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
qtpy : None
pyqt5 : None
Prior Performance
No response
Pandas version checks
I have checked that this issue has not already been reported.
I have confirmed this issue exists on the latest version of pandas.
I have confirmed this issue exists on the main branch of pandas.
Reproducible Example
import pandas as pd
import numpy as np
import timeit
n = 1_000_000
df = pd.DataFrame({"a": np.random.randn(n)})
df.index.name = "idx"
runs = 20
t1 = timeit.timeit(lambda: df.sort_index(), number=runs) / runs * 1000
t2 = timeit.timeit(lambda: df.sort_index(level="idx"), number=runs) / runs * 1000
print(f"pandas version: {pd.version}")
print(f"sort_index() : {t1:.2f} ms")
print(f"sort_index(level='idx') : {t2:.2f} ms")
print(f"overhead ratio : {t2 / t1:.1f}x")
Installed Versions
Details
INSTALLED VERSIONS
commit : aac1998
python : 3.13.7
python-bits : 64
OS : Darwin
OS-release : 24.6.0
Version : Darwin Kernel Version 24.6.0: Wed Nov 5 21:32:38 PST 2025; root:xnu-11417.140.69.705.2~1/RELEASE_ARM64_T6031
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0+untagged.3.gaac1998.dirty
numpy : 2.4.2
dateutil : 2.9.0.post0
pip : 25.2
Cython : 3.2.4
sphinx : None
IPython : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : 6.151.9
gcsfs : None
jinja2 : None
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
psycopg2 : None
pymysql : None
pyarrow : 23.0.1
pyiceberg : None
pyreadstat : None
pytest : 9.0.2
python-calamine : None
pytz : 2026.1.post1
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
qtpy : None
pyqt5 : None
Prior Performance
No response