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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.
Reproducible Example
importmatplotlib.pyplotaspltimportpandasaspddf=pd.DataFrame([(30, 10, 10), (20, 20, 20), (10, 30, 30)], columns=list('ABC'))
df.plot(subplots= [('A','B')],kind="bar", stacked=True, title=["A&B","C", "Needs another title despite no title here, removing this will error"])
print(df)
# print(pd.show_versions())plt.show()
Issue Description
df.plot() has a hard coded check to make sure there are the same number of titles when using with the "subplots" parameter, however subplots allows for multiple columns to be represented on one plot, so there are scenarios where the number of plots is less than the check for the number of titles
Expected Behavior
You shouldn't need to purposefully make empty titles up to the number of columns, the check should be run on the number of subplots
Installed Versions
INSTALLED VERSIONS
------------------
commit : 0691c5c
python : 3.11.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : AMD64 Family 25 Model 33 Stepping 2, AuthenticAMD
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United States.1252
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
df.plot() has a hard coded check to make sure there are the same number of titles when using with the "subplots" parameter, however subplots allows for multiple columns to be represented on one plot, so there are scenarios where the number of plots is less than the check for the number of titles
Expected Behavior
You shouldn't need to purposefully make empty titles up to the number of columns, the check should be run on the number of subplots
Installed Versions
pandas : 2.2.3
numpy : 1.24.2
pytz : 2025.1
dateutil : 2.8.2
pip : 25.0
Cython : None
sphinx : None
IPython : 8.12.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.3
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.2
lxml.etree : 5.3.0
matplotlib : 3.10.0
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 2.0.9
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.1
qtpy : None
pyqt5 : None
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