BUG: DataFrame.update changes type of updated values #42891
Description
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Code Sample, a copy-pastable example
import pandas as pd
df1 = pd.DataFrame.from_dict({"A": [1, 2, 3]})
df2 = pd.DataFrame.from_dict({"A": [4, 5]})
print(df1["A"])
df1.update(df2)
print(df1["A"])Output:
# df1 before the update
0 1
1 2
2 3
Name: A, dtype: int64
# df1 after the update
0 4.0
1 5.0
2 3.0
Name: A, dtype: float64
Problem description
Update of int columns changes their type to float, that is unexpected behavior. And this happens only if the other dataframe does not have all indices of this dataframe. I would expect the type to be conserved...
Expected Output
Output of pd.show_versions()
INSTALLED VERSIONS
commit : 2cb9652
python : 3.8.1.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-957.el7.x86_64
Version : #1 SMP Thu Oct 4 20:48:51 UTC 2018
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 1.2.4
numpy : 1.19.5
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 49.6.0.post20210108
Cython : 0.29.15
pytest : 5.3.5
hypothesis : None
sphinx : 3.4.3
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.12.0
pandas_datareader: None
bs4 : 4.8.2
bottleneck : 1.3.2
fsspec : 2021.06.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : None
tables : None
tabulate : None
xarray : 0.16.2
xlrd : None
xlwt : None
numba : None
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