ENH: Passing a single value to .describe(percentiles = [0.25]) returns 25th- and 50th-percentile

[ZenithClown]

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 numpy as np
import pandas as pd

# creating a single series dataframe
frame = pd.DataFrame(np.array([1, 2, 3, 4, 5, 100]))

# getting the describe with single percentile value
frame.describe(percentiles = [0.25])

Issue Description

Using a single percentile value below 50 for percentiles for data frame describe function returns 50th percentile data by default, while the same is not reflected when the value is more than 50.

# considering the above dataframe in example
>>> frame.describe(percentiles = [0.25])
                0
count    6.000000
mean    19.166667
std     39.625329
min      1.000000
25%      2.250000
50%      3.500000
max    100.000000
>>> frame.describe(percentiles = [0.35])
                0
count    6.000000
mean    19.166667
std     39.625329
min      1.000000
35%      2.750000
50%      3.500000
max    100.000000
>>> frame.describe(percentiles = [0.51])
                0
count    6.000000
mean    19.166667
std     39.625329
min      1.000000
50%      3.500000
51%      3.550000
max    100.000000

Expected Behavior

Should return only given percentile value instead.

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.12.4
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_India.1252

pandas : 2.2.3
numpy : 2.2.0
pytz : 2024.2
dateutil : 2.9.0.post0
pip : 24.1
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

[rhshadrach]

Thanks for the report. This goes back to ivanovmg@843aa60 and is indeed intentional.

But it is certainly not well documented, and I'm supportive of removing the behavior where we always include 0.5.

[kevkle]

take