BUG: Resampler.quantile produce inconsistent results when interpolation='nearest' and q=0.5

[henrykwong]

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Reproducible Example

import pandas as pd

df = pd.DataFrame({'x': [i for i in range(100)]})
df.index = pd.to_datetime(df['x'], unit='s')

res1 = df.resample('{}S'.format(n)).apply(lambda x: x.quantile(0.5, interpolation='nearest')).iloc[0][0]
res2 = df.resample('{}S'.format(n)).quantile(0.5, interpolation='nearest').iloc[0][0]
print("result from Resample.apply(lambda x: x.quantile(0.5, interpolation='nearest'): \t{}".format(res1))
print("result from Resample.quantile(q=0.5, interpolation='nearest'): \t{}".format(res2))

Issue Description

Resample.quantile(q=0.5, interpolation='nearest) and Resample.apply(lambda x: x.quantile(0.5, interpolation='nearest) produce different results. Behaviours were consistent when using other interpolation method, i.e. {‘linear’, ‘lower’, ‘higher’, ‘midpoint’} OR when q!=0.5

Expected Behavior

Actual result:
result from Resample.apply(lambda x: x.quantile(0.5, interpolation='nearest'): 50
result from Resample.quantile(q=0.5, interpolation='nearest'): 49

Expected result:
result from Resample.apply(lambda x: x.quantile(0.5, interpolation='nearest'): 50
result from Resample.quantile(q=0.5, interpolation='nearest'): 50

Installed Versions

INSTALLED VERSIONS

commit : e8093ba
python : 3.8.8.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.0-41-generic
Version : #44~20.04.1-Ubuntu SMP Fri Jun 24 13:27:29 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 1.4.3
numpy : 1.22.3
pytz : 2021.3
dateutil : 2.8.2
setuptools : 52.0.0.post20210125
pip : 21.0.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.4.3
lxml.etree : 4.6.3
html5lib : None
pymysql : 1.0.2
psycopg2 : None
jinja2 : 3.0.3
IPython : 8.0.1
pandas_datareader: 0.10.0
bs4 : 4.10.0
bottleneck : None
brotli :
fastparquet : None
fsspec : None
gcsfs : None
markupsafe : 2.0.1
matplotlib : 3.4.3
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.7.3
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None

[attack68]

Can I ask if this is a case of up/downcasting. Similar issues were observed in discussion here: #46282

[rhshadrach]

This looks to be an inconsistency in groupby.quantile:

ser = pd.Series([0, 1, 2, 3])
print(ser.quantile(0.5, interpolation="nearest"))
# 2
print(ser.groupby([0, 0, 0, 0]).quantile(0.5, interpolation="nearest"))
# 0    1
# dtype: int64

due to this line:

pandas/pandas/_libs/groupby.pyx

Line 1287 in 612823e

if frac > .5 or (frac == .5 and q_val > .5): # Always OK?

PRs to fix are welcome!