BUG: RuntimeWarning emitted when computing quantile on all pd.NA Series

[jrbourbeau]

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 pandas as pd
s = pd.Series([pd.NA, pd.NA], dtype="Int64")
result = s.quantile([0.1, 0.5])
print(f"{result = }")

Issue Description

When running the above snippet the following RuntimeWarning is emitted

/Users/james/mambaforge/envs/dask-py39/lib/python3.9/site-packages/pandas/core/array_algos/quantile.py:207: RuntimeWarning: invalid value encountered in cast
  and (result == result.astype(values.dtype, copy=False)).all()

This appears to be a result of this change https://numpy.org/doc/stable/release/1.24.0-notes.html#numpy-now-gives-floating-point-errors-in-casts in the latest numpy=1.24 release (warnings aren't emitted when using older version of numpy).

I should also note that this seems to only impact Series that only contain pd.NA. If I, for example, use s = pd.Series([1, 2, 3, pd.NA], dtype="Int64") in the above snippet no warning is emitted.

Expected Behavior

Naively I wouldn't expect a warning to be emitted to pandas users. This seems like the result of an internal implementation detail.

Installed Versions

INSTALLED VERSIONS
------------------
commit           : 8dab54d6573f7186ff0c3b6364d5e4dd635ff3e7
python           : 3.9.15.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 22.2.0
Version          : Darwin Kernel Version 22.2.0: Fri Nov 11 02:08:47 PST 2022; root:xnu-8792.61.2~4/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.5.2
numpy            : 1.24.0
pytz             : 2022.6
dateutil         : 2.8.2
setuptools       : 59.8.0
pip              : 22.3.1
Cython           : None
pytest           : 7.2.0
hypothesis       : None
sphinx           : 4.5.0
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.1.2
IPython          : 8.7.0
pandas_datareader: None
bs4              : 4.11.1
bottleneck       : None
brotli           :
fastparquet      : 2022.11.0
fsspec           : 2022.11.0
gcsfs            : None
matplotlib       : 3.6.2
numba            : None
numexpr          : 2.8.3
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 10.0.1
pyreadstat       : None
pyxlsb           : None
s3fs             : 2022.11.0
scipy            : 1.9.3
snappy           :
sqlalchemy       : 1.4.46
tables           : 3.7.0
tabulate         : None
xarray           : 2022.9.0
xlrd             : None
xlwt             : None
zstandard        : None
tzdata           : None

[phofl]

Adding milestone 1.5.3 for now