Dot product of two integer series is cast to float

[Wainberg]

Checks

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

• I have confirmed this bug exists on the latest version of Polars.

Reproducible example

>>> pl.Series([1,2,3]) @ pl.Series([4,5,6])
32.0
>>> pl.Series([1,2,3]).dot(pl.Series([4,5,6]))
32.0

Log output

No response

Issue description

The dot product of two integer series is a float when using either @ or dot.

Expected behavior

The dot product should be an integer.

Installed versions

--------Version info---------
Polars:              0.19.12
Index type:          UInt32
Platform:            Linux-4.4.0-22621-Microsoft-x86_64-with-glibc2.35
Python:              3.11.6 | packaged by conda-forge | (main, Oct  3 2023, 10:40:35) [GCC 12.3.0]

----Optional dependencies----
adbc_driver_sqlite:  0.7.0
cloudpickle:         3.0.0
connectorx:          0.3.2
deltalake:           0.10.1
fsspec:              2023.10.0
gevent:              23.9.1
matplotlib:          3.8.0
numpy:               1.26.1
openpyxl:            3.1.2
pandas:              2.1.2
pyarrow:             13.0.0
pydantic:            2.4.2
pyiceberg:           0.5.0
pyxlsb:              1.0.10
sqlalchemy:          2.0.22
xlsx2csv:            0.8.1
xlsxwriter:          3.1.9

[Wainberg]

The same thing happens with pow, with the additional problem that string and boolean columns are also automatically cast to float:

>>> pl.DataFrame({'a': [1, 2, 3], 'b': ['4', '5', '6'], 'c': [True, False, True]}).with_columns(pl.all() ** 2)
 a    b     c
 1.0  16.0  1.0
 4.0  25.0  0.0
 9.0  36.0  1.0
shape: (3, 3)
>>> pl.DataFrame({'a': [1, 2, 3], 'b': ['4', '5', '6'], 'c': [True, False, True]}).with_columns(pl.all().pow(2))
 a    b     c
 1.0  16.0  1.0
 4.0  25.0  0.0
 9.0  36.0  1.0
shape: (3, 3)