.first behind .sort_by.slice gets wrong result.

[PierXuY]

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(
    {"name": list("abcdef"), "age": [21, 31, 32, 53, 45, 26], "country": list("AABBBC")}
)
print(df)

out1 = df.group_by("country").agg(
    pl.col("name").sort_by("age").slice(2, 1)
).sort("country")
print(out1)

out2 = df.group_by("country").agg(
    pl.col("name").sort_by("age").slice(2,1).first()  # only add .first(), but get wrong result.

).sort("country")
print(out2)

Log output

shape: (6, 3)
┌──────┬─────┬─────────┐
│ name ┆ age ┆ country │
│ ---  ┆ --- ┆ ---     │
│ str  ┆ i64 ┆ str     │
╞══════╪═════╪═════════╡
│ a    ┆ 21  ┆ A       │
│ b    ┆ 31  ┆ A       │
│ c    ┆ 32  ┆ B       │
│ d    ┆ 53  ┆ B       │
│ e    ┆ 45  ┆ B       │
│ f    ┆ 26  ┆ C       │
└──────┴─────┴─────────┘
shape: (3, 2)
┌─────────┬───────────┐
│ country ┆ name      │
│ ---     ┆ ---       │
│ str     ┆ list[str] │
╞═════════╪═══════════╡
│ A       ┆ []        │
│ B       ┆ ["d"]     │
│ C       ┆ []        │
└─────────┴───────────┘
shape: (3, 2)
┌─────────┬──────┐
...
│ A       ┆ null │
│ B       ┆ e    │
│ C       ┆ null │
└─────────┴──────┘

Issue description

The result of .first() should be d in list of out1, not e.

Expected behavior

get correctly result

Installed versions

--------Version info---------
Polars:               1.5.0
Index type:           UInt32
Platform:             Windows-10-10.0.22631-SP0
Python:               3.10.11 (tags/v3.10.11:7d4cc5a, Apr  5 2023, 00:38:17) [MSC v.1929 64 bit (AMD64)]

----Optional dependencies----
adbc_driver_manager:  1.1.0
cloudpickle:          3.0.0
connectorx:           0.3.3
deltalake:            0.19.0
fastexcel:            0.11.5
fsspec:               2024.6.1
gevent:               24.2.1
great_tables:         0.10.0
hvplot:               0.10.0
matplotlib:           3.9.2
nest_asyncio:         1.6.0
numpy:                2.0.1
openpyxl:             3.1.5
pandas:               2.2.2
pyarrow:              17.0.0
pydantic:             2.8.2
pyiceberg:            0.7.0
sqlalchemy:           2.0.32
torch:                <not installed>
xlsx2csv:             0.8.3
xlsxwriter:           3.2.0

[PierXuY]

Is this a bug?

[cmdlineluser]

I believe so.

If we change the example slightly, we actually get values from the wrong group.

df = pl.DataFrame(
    {"name": list("abcdef"), "age": [31, 21, 32, 53, 45, 26], "country": list("AABBBC")}
)

df.group_by("country", maintain_order=True).agg(
    sort_by = pl.col("name").sort_by("age"),
    x =  pl.col("name").sort_by("age").slice(0, 1).first(),
    y =  pl.col("name").sort_by("age").slice(1, 1).first(),
    z =  pl.col("name").sort_by("age").slice(2, 1).first()
)

# shape: (6, 3)
# ┌──────┬─────┬─────────┐
# │ name ┆ age ┆ country │
# │ ---  ┆ --- ┆ ---     │
# │ str  ┆ i64 ┆ str     │
# ╞══════╪═════╪═════════╡
# │ a    ┆ 31  ┆ A       │
# │ b    ┆ 21  ┆ A       │
# │ c    ┆ 32  ┆ B       │
# │ d    ┆ 53  ┆ B       │
# │ e    ┆ 45  ┆ B       │
# │ f    ┆ 26  ┆ C       │
# └──────┴─────┴─────────┘

# shape: (3, 5)
# ┌─────────┬─────────────────┬─────┬──────┬──────┐
# │ country ┆ sort_by         ┆ x   ┆ y    ┆ z    │
# │ ---     ┆ ---             ┆ --- ┆ ---  ┆ ---  │
# │ str     ┆ list[str]       ┆ str ┆ str  ┆ str  │
# ╞═════════╪═════════════════╪═════╪══════╪══════╡
# │ A       ┆ ["b", "a"]      ┆ b   ┆ c    ┆ null │ # <- value `c` belongs to country `B`
# │ B       ┆ ["c", "e", "d"] ┆ c   ┆ d    ┆ e    │ # <- wrong order
# │ C       ┆ ["f"]           ┆ f   ┆ null ┆ null │
# └─────────┴─────────────────┴─────┴──────┴──────┘