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But still, you should be able to replace general Python objects in an object dtype column? (the example using object() is of course a bit fake, but in can be any custom Python class objects)
I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
(optional) I have confirmed this bug exists on the master branch of pandas.
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Code Sample, a copy-pastable example
Problem description
In pandas 1.0.5
In pandas 1.1.2
Is this expected behavior or bug?
Expected Output
Output of
pd.show_versions()
INSTALLED VERSIONS
commit : 2a7d332
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 4.4.171-70.1
Version : #1 SMP Thu Jan 31 10:46:27 UTC 2019
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.2
numpy : 1.16.6
pytz : 2020.1
dateutil : 2.8.1
pip : None
setuptools : 44.1.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
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