ENH: Support errors="ignore" for astype with pyarrow types

[mdruiter]

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Reproducible Example

import pandas as pd
mydf = pd.DataFrame({'col': [17000000]}, dtype='int32[pyarrow]')
mydf.astype('float[pyarrow]', errors='ignore')

Issue Description

I have a DataFrame containing integers and floating point numbers, in separate columns. Before stacking them, I tried converting all values to (single precision) floats. I got an exception, because PyArrow happens to guard against precision loss. Fair enough. But even when I add errors='ignore', I get the error:

ArrowInvalid: Integer value 17000000 not in range: -16777216 to 16777216

The minimal reproducing example contains only one column and one row. Interestingly enough, converting per column as Series produces no error.

Expected Behavior

I expect to be able to convert PyArrow int32 values to PyArrow floats using astype.

Installed Versions

[path]\Lib\site-packages_distutils_hack_init_.py:33: UserWarning: Setuptools is replacing distutils.
warnings.warn("Setuptools is replacing distutils.")

INSTALLED VERSIONS

commit : e86ed37
python : 3.11.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22621
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : Dutch_Netherlands.1252

pandas : 2.1.1
numpy : 1.26.0
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.2.1
Cython : 3.0.2
pytest : 7.4.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 8.16.1
pandas_datareader : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.0
numba : None
numexpr : 2.8.7
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 13.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.3
sqlalchemy : 2.0.21
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
zstandard : 0.21.0
tzdata : 2023.3
qtpy : None
pyqt5 : None

[yuanx749]

take

[yuanx749]

In the DataFrame.astype source code below, I think perhaps the errors argument is missing in L6572, which should be ser.astype(dtype, copy=copy, errors=errors) instead? @mroeschke

pandas/pandas/core/generic.py

Lines 6563 to 6572 in fe07fd5

	elif is_extension_array_dtype(dtype) and self.ndim > 1:
	# TODO(EA2D): special case not needed with 2D EAs
	dtype = pandas_dtype(dtype)
	if isinstance(dtype, ExtensionDtype) and all(
	arr.dtype == dtype for arr in self._mgr.arrays
	):
	return self.copy(deep=copy)
	# GH 18099/22869: columnwise conversion to extension dtype
	# GH 24704: self.items handles duplicate column names
	results = [ser.astype(dtype, copy=copy) for _, ser in self.items()]

This seems more like a bug, since Series.astype with errors="ignore" suppress the exception, and returns original object.