Description
Pandas version checks
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I have checked that this issue has not already been reported.
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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 scipy
import pandas as pd
coo = scipy.sparse.coo_matrix([[False,True],[True,False]])
pd.DataFrame.sparse.from_spmatrix(coo) # results in FutureWarning
coo = scipy.sparse.coo_matrix([[0,1],[1,0]])
pd.DataFrame.sparse.from_spmatrix(coo) # no warningsIssue Description
Attempting to use from_spmatrix() with a boolean-type scipy.sparse matrix raises a warning about arbitrary scalar fill_value:
FutureWarning: Allowing arbitrary scalar fill_value in SparseDtype is deprecated. In a future version, the fill_value must be a valid value for the SparseDtype.subtype.
pd.DataFrame.sparse.from_spmatrix(coo)
but using sparse integer dtype for the scipy matrix does not. I don't understand why this occurs, but it seems like from_spmatrix should be able to handle both of these scenarios. Also, there is no argument to from_spmatrix to specify a type, so it is unclear what the user should do about this future warning if anything.
Expected Behavior
No warning, uses dtype matching input
Installed Versions
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.9.13.final.0
python-bits : 64
OS : Darwin
OS-release : 21.6.0
Version : Darwin Kernel Version 21.6.0: Mon Aug 22 20:19:52 PDT 2022; root:xnu-8020.140.49~2/RELEASE_ARM64_T6000
machine : arm64
processor : arm
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 : 70.1.0
pip : 22.1.2
Cython : None
pytest : 8.2.2
hypothesis : None
sphinx : 7.3.7
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.4
IPython : 8.18.1
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.6.0
gcsfs : None
matplotlib : 3.9.0
numba : 0.60.0
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.13.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None