Closed
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 pandas as pd
df = pd.DataFrame({"x": [1, 2, 3], "y": ["foo", "bar", "baz"]})
df_empty = df.iloc[:0]
print(f"{df.convert_dtypes().dtypes = }") # works as expected (i.e. dtype is `string[python]`)
print(f"{df_empty.convert_dtypes().dtypes = }") # `y` has dtype `object` even though `convert_string=True`
with pd.option_context("mode.dtype_backend", "pyarrow"):
print(f"{df.convert_dtypes().dtypes = }") # works as expected (i.e. dtype is `string[pyarrow]`)
print(f"{df_empty.convert_dtypes().dtypes = }") # This errors with `pyarrow.lib.ArrowNotImplementedError: Unsupported numpy type 17`Issue Description
When calling DataFrame.convert_dtypes() on an empty DataFrame I noticed that issues with handling object dtypes with both the pandas and pyarrow dtype backends.
When using the pandas dtype backend, object columns aren't converted to string[python], they instead remain object (even though convert_string=True). When using the pyarrow backend, we get the following error:
Traceback (most recent call last):
File "/Users/james/projects/dask/dask/test-convert-dtypes.py", line 11, in <module>
print(f"{df_empty.convert_dtypes().dtypes = }") # `y` has dtype `object` even though `convert_string=True`
File "/Users/james/projects/pandas-dev/pandas/pandas/core/generic.py", line 6660, in convert_dtypes
results = [
File "/Users/james/projects/pandas-dev/pandas/pandas/core/generic.py", line 6661, in <listcomp>
col._convert_dtypes(
File "/Users/james/projects/pandas-dev/pandas/pandas/core/series.py", line 5469, in _convert_dtypes
inferred_dtype = convert_dtypes(
File "/Users/james/projects/pandas-dev/pandas/pandas/core/dtypes/cast.py", line 1124, in convert_dtypes
pa_type = to_pyarrow_type(base_dtype)
File "/Users/james/projects/pandas-dev/pandas/pandas/core/arrays/arrow/array.py", line 145, in to_pyarrow_type
pa_dtype = pa.from_numpy_dtype(dtype)
File "pyarrow/types.pxi", line 3330, in pyarrow.lib.from_numpy_dtype
File "pyarrow/error.pxi", line 121, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Unsupported numpy type 17cc @mroeschke @phofl for visibility
Expected Behavior
I would expect convert_dtypes to behave the same, even if the DataFrame is empty.
Installed Versions
INSTALLED VERSIONS
------------------
commit : 7f2aa8f46a4a36937b1be8ec2498c4ff2dd4cf34
python : 3.10.4.final.0
python-bits : 64
OS : Darwin
OS-release : 22.2.0
Version : Darwin Kernel Version 22.2.0: Fri Nov 11 02:08:47 PST 2022; root:xnu-8792.61.2~4/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.0.0.dev0+1309.g7f2aa8f46a
numpy : 1.24.1
pytz : 2022.1
dateutil : 2.8.2
setuptools : 59.8.0
pip : 22.0.4
Cython : None
pytest : 7.1.3
hypothesis : None
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.2.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli :
fastparquet : 2022.12.1.dev6
fsspec : 2023.1.0+5.g012816b
gcsfs : None
matplotlib : 3.5.1
numba : None
numexpr : 2.8.0
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 11.0.0.dev316
pyreadstat : None
pyxlsb : None
s3fs : 2022.10.0
scipy : 1.9.0
snappy :
sqlalchemy : 1.4.35
tables : 3.7.0
tabulate : None
xarray : 2022.3.0
xlrd : None
zstandard : None
tzdata : None
qtpy : None
pyqt5 : None