BUG: Adding two series with pd.Series.add can change the dtype in unexpected ways.

[kbruegge]

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
idx = pd.MultiIndex.from_arrays(
    [["a", "a", "a", "b", "b", "b"], [1, 2, 3, 1, 2, 3],], 
    names=["foo", "bar"]
)
s = pd.Series(
    index=idx,
    data=range(6),
    name="otto"
) # this has int64 dtype which is what i want 

new_s = pd.Series(
    index=pd.Index(["a", "b"], name="foo"),
    data=[100, -100 ],
    name="otto"
) # also contains int64

s.add(new_s, fill_value=0) # also has int64 dtype which is correct since i'm adding ints to ints


another_s = pd.Series(
    index=pd.Index(["a", "c"], name="foo"),
    data=[100, 50 ],
    name="otto"
) # a new series of ints but this time there is a new entry in the index which didn't exist in s

s.add(another_s, fill_value=0) # this time the dtype changed to float64. which is wrong and creates errors downstream for me

Issue Description

When adding together pd.Series with overlapping indices sometimes the dtype changes from int64 to float64 When using s.add(another_s, fill_value=0) To be clear: the numbers are correct and the results are what I expect. Except for the dtype now being float.

Expected Behavior

Using s + another_s produces nan if the indices don't all match exactly which in turn would change the dtype form int to float. However when using add(_, fill_value=0) I'd expect the dtype to remain int64.

Installed Versions

INSTALLED VERSIONS

commit : 2a953cf
python : 3.11.5.final.0
python-bits : 64
OS : Darwin
OS-release : 23.2.0
Version : Darwin Kernel Version 23.2.0: Wed Nov 15 21:55:06 PST 2023; root:xnu-10002.61.3~2/RELEASE_ARM64_T6020
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8

pandas : 2.1.3
numpy : 1.26.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 67.6.1
pip : 23.1
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 : 8.17.2
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.2
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.4
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[VISWESWARAN1998]

I checked-in latest changes in main branch and executed your code. I still see data type of variable s as int64.

Perhaps the issue could have been fixed in main.