BUG: clip function works with float arrays but not ExtendedArrays (similar problem to #45778)

[MichaelTiemannOSC]

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
import pint_pandas
from pint_pandas import PintArray as PA_

xx = pd.DataFrame(PA_([1.,2.,3.],dtype='pint[m]'))
yy = PA_([10.,10.,10.],dtype='pint[m]')
zz = PA_([0.,0.,0.],dtype='pint[m]')

# Clip 1,2,3 against lower bound of 10,10,10 results in 10,10,10
xx.clip(lower=yy, axis=0)
#       0
# 0  10.0
# 1  10.0
# 2  10.0

# Clip 1,2,3 against lower bound of 0,0,0 should result in 1,2,3
xx.clip(lower=zz, axis=0)
# *** IndexError: index 0 is out of bounds for axis 0 with size 0

Issue Description

This problem smacks of the recently merged regression identified here: #45778

But this is not a problem with the .loc indexer, but elsewhere. Most likely the where function in blocks.py, line 1634 in the 1.4.0 release. Maybe the fix is very simple: in function (def where(self, other, cond, errors="raise") -> list[Block]:
) replace

        try:
            result[icond] = set_other

with

        try:
            if icond.any():
                result[icond] = set_other

Expected Behavior

I expect that a clip action that is supposed to do nothing will do nothing, not throw an error about a zero-sized array that's unable to handle a zero-sized update of nothingness.

Installed Versions

INSTALLED VERSIONS

commit : 66e3805
python : 3.9.9.final.0
python-bits : 64
OS : Darwin
OS-release : 21.3.0
Version : Darwin Kernel Version 21.3.0: Wed Jan 5 21:37:58 PST 2022; root:xnu-8019.80.24~20/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.3.5
numpy : 1.22.0
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 60.3.1
Cython : 0.29.26
pytest : None
hypothesis : None
sphinx : 4.3.2
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.31.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : 2.8.0
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : None

[MichaelTiemannOSC]

This was true for version 1.3.5 but not yet checked for 1.4.1.

[MichaelTiemannOSC]

Apparently fixed since 1.3.5. Good work!