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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
frompathlibimportPathimportnumpyasnpimportpandasaspdpath=Path("file.csv")
# Empty values in MultiIndex for both index & columnsdf=pd.DataFrame(
np.arange(6).reshape((2, 3)),
columns=pd.MultiIndex.from_tuples((("a", ""), ("b", ""), ("b", "b2"))),
index=pd.MultiIndex.from_tuples((("i1", ""), ("i2", ""))),
)
df.to_csv(path)
# CSV has empty cells in multiindex; just like the df:# , ,a ,b ,b# , , , ,b2# i1 , ,0 ,1 ,2# i2 , ,3 ,4 ,5df_read=pd.read_csv(path, header=[0, 1], index_col=[0, 1])
# Reading from CSV fills multiindex xwith "Unnamed: ..."# , ,a ,b ,b# , ,Unnamed: 2_level_1 ,Unnamed: 3_level_1 ,b2# i1 , ,0 ,1 ,2# i2 , ,3 ,4 ,5
Issue Description
Hi,
Closely related to #51252#51824#50953. I opened a new issue as it's not exactly the same example, but feel free to close if it's not relevant. Not even sure it's a bug or not, sorry if i'm mistaking.
When reading a dataframe from CSV, if the columns have empty values, it gets filled with "Unnamed: ..." pattern. This makes sense for regular 1D columns, as they need to be unique. When it comes to columns using multiindex, the uniqueness can be ensured even with empty values, if the other levels are different. Current implementation uses "Unnamed: ..." in both cases.
When reading index with Multiindex, empty values don't get replaced. The index read from CSV in the minimal example is identical to the initial index.
Expected Behavior
I would expect consistency in the handling of MultiIndex by index & columns. Maybe it's not feasible due to the uniqueness required by columns & not by index
Empty values should be left unfilled if the index remains unique. This would require an identification of duplicates in the multiindex before filling the values, thus losing consistency within the handling of MultiIndex for columns
Installed Versions
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.12.2.final.0
python-bits : 64
OS : Windows
OS-release : 11
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : fr_FR.cp1252
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
Hi,
Closely related to #51252 #51824 #50953. I opened a new issue as it's not exactly the same example, but feel free to close if it's not relevant. Not even sure it's a bug or not, sorry if i'm mistaking.
When reading a dataframe from CSV, if the columns have empty values, it gets filled with
"Unnamed: ..."
pattern. This makes sense for regular 1D columns, as they need to be unique. When it comes to columns using multiindex, the uniqueness can be ensured even with empty values, if the other levels are different. Current implementation uses"Unnamed: ..."
in both cases.When reading index with Multiindex, empty values don't get replaced. The index read from CSV in the minimal example is identical to the initial index.
Expected Behavior
I would expect consistency in the handling of MultiIndex by index & columns. Maybe it's not feasible due to the uniqueness required by columns & not by index
Empty values should be left unfilled if the index remains unique. This would require an identification of duplicates in the multiindex before filling the values, thus losing consistency within the handling of MultiIndex for columns
Installed Versions
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.12.2.final.0
python-bits : 64
OS : Windows
OS-release : 11
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : fr_FR.cp1252
pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : None
pip : 24.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None
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