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
pd.DataFrame(data=[1, 2, 3], columns=['value']).describe(percentiles=[0.29, 0.57, 0.58])
value
count 3.00
mean 2.00
std 1.00
min 1.00
29.0% 1.58
50% 2.00
57.0% 2.14
58.0% 2.16
max 3.00Issue Description
The indexes ['29.0%', '57.0%', '58.0%'] should be named as ['29%', '57%', '58%'].
Expected Behavior
pd.DataFrame(data=[1, 2, 3], columns=['value']).describe(percentiles=[0.29, 0.57, 0.58]).index
# Output:
Index(['count', 'mean', 'std', 'min', '29.0%', '50%', '57.0%', '58.0%', 'max'], dtype='object')
# Expected:
Index(['count', 'mean', 'std', 'min', '29%', '50%', '57%', '58%', 'max'], dtype='object')
Installed Versions
INSTALLED VERSIONS
commit : 06d2301
python : 3.9.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.13.0-30-generic
Version : #33-Ubuntu SMP Fri Feb 4 17:03:31 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_IL
LOCALE : en_IL.UTF-8
pandas : 1.4.1
numpy : 1.22.2
pytz : 2021.3
dateutil : 2.8.2
pip : 22.0.3
setuptools : 59.8.0
Cython : None
pytest : None
hypothesis : None
sphinx : 4.4.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.8.0
html5lib : None
pymysql : None
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 7.32.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
fsspec : 2022.02.0
gcsfs : None
matplotlib : 3.5.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : 2022.02.0
scipy : 1.8.0
sqlalchemy : 1.4.31
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None