sum_horizontal + list.explode PanicException instead of ShapeError

[cmdlineluser]

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

import polars as pl

df = pl.DataFrame({"a": [[1, 2], None], "b": [[3, 4], [5, 6]]})

df.select(pl.sum_horizontal(pl.all().list.explode()))
# thread '<unnamed>' panicked at crates/polars-core/src/chunked_array/ops/arity.rs:865:14:
# Cannot apply operation on arrays of different lengths
# PanicException: Cannot apply operation on arrays of different lengths

Log output

No response

Issue description

It seems to happen for mean_horizontal also.

All other horizontal methods produce a ShapeError.

df.select(pl.all_horizontal(pl.all().list.explode()))
# ShapeError: cannot evaluate two Series of different lengths (3 and 4)
# Error originated in expression: '[(col("a").explode()) & (col("b").explode())]'

Expected behavior

Error instead of panic.

Installed versions

--------Version info---------
Polars:               1.10.0
Index type:           UInt32
Platform:             macOS-13.6.1-arm64-arm-64bit
Python:               3.12.2 (main, Feb  6 2024, 20:19:44) [Clang 15.0.0 (clang-1500.1.0.2.5)]

----Optional dependencies----
adbc_driver_manager:  <not installed>
cloudpickle:          <not installed>
connectorx:           <not installed>
deltalake:            <not installed>
fastexcel:            <not installed>
fsspec:               <not installed>
gevent:               <not installed>
great_tables:         <not installed>
hvplot:               <not installed>
matplotlib:           <not installed>
nest_asyncio:         <not installed>
numpy:                1.26.4
openpyxl:             <not installed>
pandas:               2.2.1
pyarrow:              15.0.2
pydantic:             <not installed>
pyiceberg:            <not installed>
sqlalchemy:           <not installed>
torch:                <not installed>
xlsx2csv:             <not installed>
xlsxwriter:           <not installed>