Calculating the mean of a Decimal column returns nulls

[knutmerket]

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
pl.Config.activate_decimals(True)

df = pl.DataFrame(
    {
        "a": [1, 8, 3],
        "b": [-16840000.8900, 16840000.0000, 30000.0000],
        "c": ["foo", "bar", "foo"],
    },
)

(df
.with_columns(
    d=pl.col("b").cast(pl.Decimal())
)
.group_by("c").agg(mean=pl.col("d").mean())
)

┌─────┬───────────────┐
│ c ┆ mean │
│ --- ┆ --- │
│ str ┆ decimal[38,0] │
╞═════╪═══════════════╡
│ foo ┆ null │
│ bar ┆ null │
└─────┴───────────────┘

Log output

Out[9]: 
shape: (2, 2)
┌─────┬───────────────┐
│ c   ┆ mean          │
│ --- ┆ ---           │
│ str ┆ decimal[38,0] │
╞═════╪═══════════════╡
│ foo ┆ null          │
│ bar ┆ null          │
└─────┴───────────────┘

Issue description

My data source is a Denodo view where one of the fields is of the Decimal (19,4) type. I read this into Polars (v. 0.20.23) using read_database(). And sure enough it's read as that data type (despite that fact that I haven't activated Decimals in the config and that none of the values that my query returns are even close to going beyond the limits of Float64, but I guess the Denodo view's dtype specification is respected).

I want to group by another column and do a calculation of the Decimal-column's mean. But this returns only nulls.

I am not sure if this is partially or fully expected with the Decimal type since it's considered "unstable".

For the actual "real world" example where I ran into this issue, I can get around it by converting the column to Float64, but that obviously wouldn't work if I had rows with values that would overflow that dtype.

Expected behavior

Actual means of the groups, not missing values.

Installed versions

--------Version info---------
Polars:               0.20.23
Index type:           UInt32
Platform:             Linux-4.14.336-256.559.amzn2.x86_64-x86_64-with-glibc2.35
Python:               3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0]

----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>
hvplot:               <not installed>
matplotlib:           <not installed>
nest_asyncio:         1.6.0
numpy:                1.26.4
openpyxl:             <not installed>
pandas:               2.2.2
pyarrow:              <not installed>
pydantic:             2.7.1
pyiceberg:            <not installed>
pyxlsb:               <not installed>
sqlalchemy:           <not installed>
xlsx2csv:             <not installed>
xlsxwriter:           <not installed>