Pandas version checks
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[x] I have checked that this issue has not already been reported.
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[x] 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 numpy as np
import pandas as pd
start_time = '2025-06-06'
end_time = '2025-06-09'
sig1 = pd.read_parquet('data1.par')
sig1 = sig1[(sig1.tradeDate >= start_time) & (sig1.tradeDate <= end_time)]
sig1 = sig1.pivot(index='tradeDate', columns='ticker', values='signal_value').fillna(0)
sig2 = pd.read_parquet('data2.par')
sig2 = sig2[(sig2.tradeDate >= start_time) & (sig2.tradeDate <= end_time)]
sig2 = sig2.pivot(index='tradeDate', columns='ticker', values='signal_value').fillna(0)
sig = sig1 + sig2
filt = pd.read_feather('filter.fea').set_index('tradeDate')
filt.index = pd.to_datetime(filt.index)
filt = filt.reindex(sig.index, columns=sig.columns)
# method 1: make a copy then filter
s1 = sig.copy()
s1.values[:] = np.where(filt == 1, s1, np.nan)
print(s1.count(axis=1))
# method 2: directly filter
sig.values[:] = np.where(filt == 1, sig, np.nan)
print(sig.count(axis=1))
Issue Description
Why not work：
sig.values[:] = np.where(filt == 1, sig, np.nan)
If using a copy, the sentence above works:
s1 = sig.copy()
s1.values[:] = np.where(filt == 1, s1, np.nan)
Expected Behavior
Both methods should work.
Installed Versions
INSTALLED VERSIONS
------------------
commit : d9cdd2ee5a58015ef6f4d15c7226110c9aab8140
python : 3.12.7.final.0
python-bits : 64
OS : Darwin
OS-release : 24.5.0
Version : Darwin Kernel Version 24.5.0: Tue Apr 22 19:48:46 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T8103
machine : arm64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 75.1.0
pip : 24.2
Cython : None
pytest : 7.4.4
hypothesis : None
sphinx : 7.3.7
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.2.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.4
IPython : 8.27.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : 1.3.7
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.6.1
gcsfs : None
matplotlib : 3.9.2
numba : 0.60.0
numexpr : 2.8.7
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
pyarrow : 16.1.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : 2024.6.1
scipy : 1.13.1
sqlalchemy : 2.0.34
tables : 3.10.1
tabulate : 0.9.0
xarray : 2023.6.0
xlrd : None
zstandard : 0.23.0
tzdata : 2023.3
qtpy : 2.4.1
pyqt5 : None
Comment From: Allan0820
take