BUG: running apply on a cell with NoneType returns error.

[Ali-Flt]

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 as pd
pre_df = pd.DataFrame(...)

pre_df['row_with_nonetype'].apply(lambda x: func(x))

Issue Description

Because apply is checking the len(s) here:

....pandas/core/apply.py:1123), in SeriesApply.apply(self)
   1120     return self.apply_str()
   1122 # self.f is Callable
...
--> 907     index = default_index(len(s))
    909 if id(index) in indexer_cache:
    910     indexer = indexer_cache[id(index)]

when s is NoneType it returns error.

Expected Behavior

No error

Installed Versions

INSTALLED VERSIONS

commit : 2e218d1
python : 3.8.16.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-146-generic
Version : #163-Ubuntu SMP Fri Mar 17 18:26:02 UTC 2023
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.5.3
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 67.6.0
pip : 23.0.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.11.0
pandas_datareader: None
bs4 : 4.11.2
bottleneck : None
brotli :
fastparquet : None
fsspec : 2023.3.0
gcsfs : None
matplotlib : 3.7.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None

[phofl]

Please post a reproducible example

[alexprincel]

Adding the exact error message observed would be helpful as well.

[Ali-Flt]

I apologize,
I believe my mistake was that I was trying to write a pandas Series into a pandas DataFrame's cell and the error put me off. The scenario was something like this:

def func(x):
    try:
        return x[1]
    except Exception:
        return x
df['new_col] = df['old_col']apply(lambda x: func(x))

Where df['old_col'] had pd.Series() in its cells, some of which were a pd.Series() with a single element = None and some others were a pd.Series() with a single element = tuple(...).
I used .item() instead and it worked:

def func(x):
    try:
        return x.item()[1]
    except Exception:
        try:
            return x[1]
        except Exception:
            try:
                return x.item()
            except Exception:
                return x
df['new_col] = df['old_col']apply(lambda x: func(x))