BUG:

[evyasonov]

Pandas version checks

• [X] I have checked that this issue has not already been reported.

• [X] I have confirmed this bug exists on the latest version of pandas.

• [X] 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 : a671b5a8bf5dd13fb19f0e88edc679bc9e15c673 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.