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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.
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))
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)
Both methods should work.
data.zip
commit : d9cdd2e 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
The text was updated successfully, but these errors were encountered:
take
Sorry, something went wrong.
I think the underlying values array is read-only, see https://pandas.pydata.org/docs/dev/user_guide/copy_on_write.html#read-only-numpy-arrays
Could you use pd.where instead?
pd.where
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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
Issue Description
Why not work:
If using a copy, the sentence above works:
Expected Behavior
Both methods should work.
Installed Versions
data.zip
INSTALLED VERSIONS
commit : d9cdd2e
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
The text was updated successfully, but these errors were encountered: