BUG:

[evyasonov]

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

import pandas, numpy

df = pandas.DataFrame([['s', 1, 2.3, 0]], columns=['str', 'int', 'flt', 'to ignore'])
df['int'] = df['int'].astype('Int64')
df['flt'] = df['flt'].astype('Float64')

columns_to_process = ['str', 'int', 'flt']

df.loc[:, columns_to_process] = df.loc[:, columns_to_process].astype(str)

Issue Description

df.loc[:, columns_to_process] = df.loc[:, columns_to_process].astype(str)

throws the following error

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
TypeError: len() of unsized object
Exception ignored in: 'pandas._libs.lib.is_string_array'
Traceback (most recent call last):
  File "C:\Users\evgeniy\AppData\Local\anaconda3\Lib\site-packages\pandas\core\arrays\numeric.py", line 162, in _coerce_to_data_and_mask
    inferred_type = lib.infer_dtype(values, skipna=True)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: len() of unsized object
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
TypeError: len() of unsized object
Exception ignored in: 'pandas._libs.lib.is_string_array'
Traceback (most recent call last):
  File "C:\Users\evgeniy\AppData\Local\anaconda3\Lib\site-packages\pandas\core\arrays\numeric.py", line 162, in _coerce_to_data_and_mask
    inferred_type = lib.infer_dtype(values, skipna=True)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: len() of unsized object

Expected Behavior

No error

Installed Versions

INSTALLED VERSIONS

commit : a671b5a
python : 3.11.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : Russian_Russia.1251

pandas : 2.1.4
numpy : 1.26.4
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : None
pytest : 7.4.0
hypothesis : None
sphinx : 5.0.2
blosc : None
feather : None
xlsxwriter : 3.2.0
lxml.etree : 4.9.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.20.0
pandas_datareader : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat: None
fastparquet : None
fsspec : 2023.10.0
gcsfs : None
matplotlib : 3.8.0
numba : 0.59.0
numexpr : 2.8.7
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 14.0.2
pyreadstat : None
pyxlsb : None
s3fs : 2023.10.0
scipy : 1.11.4
sqlalchemy : 2.0.25
tables : 3.9.2
tabulate : 0.9.0
xarray : 2023.6.0
xlrd : None
zstandard : 0.19.0
tzdata : 2023.3
qtpy : 2.4.1
pyqt5 : None

[Aloqeely]

Thanks for the report! This is fixed on the latest release of pandas (v2.2), could you update pandas and see if that resolves the problem for you?

[Aloqeely]

Going to close - feel free to re-open if the issue isn't fixed after updating.