Description
Pandas version checks
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
importpandasaspdimportpyarrowaspacol_names=pd.Series([3, 4]).astype("category").astype(pd.ArrowDtype(pa.dictionary(pa.int8(), pa.int8()))) pd.DataFrame({3: [1,2]}, columns=col_names)Issue Description
Constructing a DataFrame using a dict and Series with a numeric dictionary ArrowDtype to indicate columns results in an empty DataFrame.
Using other dtypes seems to work perfectly, e.g. category type:
col_names=pd.Series([3, 4]).astype("category") pd.DataFrame({3: [1,2]}, columns=col_names)Output:
| 3 | 4 | |
|---|---|---|
| 0 | 1 | nan |
| 1 | 2 | nan |
Using a dictionary ArrowDtype with string categories also works:
col_names=pd.Series(["3","4"]).astype("category").astype(pd.ArrowDtype(pa.dictionary(pa.int64(), pa.utf8()))) pd.DataFrame({"3": [1,2]}, columns=col_names)Output:
| "3" | "4" | |
|---|---|---|
| 0 | 1 | nan |
| 1 | 2 | nan |
This bug might seem esoteric, but it bit me when trying to .stack a DataFrame with multiindex colums composed of numeric dictionary ArrowDtype:
col_level_1= ( pd.Series([3, 4]) .astype("category") .astype(pd.ArrowDtype(pa.dictionary(pa.int64(), pa.int64()))) ) col_level_2= ( pd.Series([5, 6]) .astype("category") .astype(pd.ArrowDtype(pa.dictionary(pa.int64(), pa.int64()))) ) multicol=pd.MultiIndex.from_arrays([col_level_1, col_level_2]) df=pd.DataFrame([[1, 2], [2, 4]], columns=multicol) df.stack()Output:
Empty DataFrame Columns: [3, 4] Index: [] Expected Behavior
A DataFrame with the data provided to the constructor:
| 3 | 4 | |
|---|---|---|
| 0 | 1 | nan |
| 1 | 2 | nan |
Installed Versions
INSTALLED VERSIONS
commit : c65c8dd
python : 3.11.3.final.0
python-bits : 64
OS : Linux
OS-release : 5.19.0-43-generic
Version : #44~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon May 22 13:39:36 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.1.0.dev0+942.gc65c8ddd73
numpy : 2.0.0.dev0+84.g828fba29e
pytz : 2023.3
dateutil : 2.8.2
setuptools : 65.5.0
pip : 22.3.1
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
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 12.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None
