Nested struct column is null after pivoting DataFrame

[edm1]

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(
    {
        "foo": ["one", "two", "one", "two"],
        "bar": ["x", "x", "y", "y"],
        "baz": [
            {"a": 1, "b": {"c": 2}},
            {"a": 3, "b": {"c": 4}},
            {"a": 5, "b": {"c": 6}},
            {"a": 7, "b": {"c": 8}},
        ]
    }
)

piv = df.pivot(index="foo", columns="bar", values="baz")

print(piv)

Log output

shape: (2, 3)
┌─────┬────────────┬────────────┐
│ foo ┆ x          ┆ y          │
│ --- ┆ ---        ┆ ---        │
│ str ┆ struct[2]  ┆ struct[2]  │
╞═════╪════════════╪════════════╡
│ one ┆ {1,{null}} ┆ {5,{null}} │
│ two ┆ {3,{null}} ┆ {7,{null}} │
└─────┴────────────┴────────────┘

Issue description

Pivotting values containing a nested struct causes the nested contents to become null.

Expected behavior

Expected output

shape: (2, 3)
┌─────┬────────────┬────────────┐
│ foo ┆ x          ┆ y          │
│ --- ┆ ---        ┆ ---        │
│ str ┆ struct[2]  ┆ struct[2]  │
╞═════╪════════════╪════════════╡
│ one ┆ {1,{2}}    ┆ {5,{6}}    │
│ two ┆ {3,{4}}    ┆ {7,{8}}    │
└─────┴────────────┴────────────┘

Installed versions

--------Version info---------
Polars:               0.20.31
Index type:           UInt32
Platform:             Linux-5.15.0-1064-azure-x86_64-with-glibc2.36
Python:               3.12.3 (main, May 14 2024, 07:23:41) [GCC 12.2.0]

----Optional dependencies----
adbc_driver_manager:  <not installed>
cloudpickle:          <not installed>
connectorx:           <not installed>
deltalake:            <not installed>
fastexcel:            <not installed>
fsspec:               2024.6.0
gevent:               <not installed>
hvplot:               <not installed>
matplotlib:           3.9.0
nest_asyncio:         <not installed>
numpy:                1.26.4
openpyxl:             <not installed>
pandas:               <not installed>
pyarrow:              16.1.0
pydantic:             2.7.3
pyiceberg:            <not installed>
pyxlsb:               <not installed>
sqlalchemy:           <not installed>
torch:                2.3.0+cu121
xlsx2csv:             0.8.2
xlsxwriter:           <not installed>

[cmdlineluser]

Can reproduce.

In case it may be a useful datapoint for debugging, transpose also seems to lose the inner values.

>>> df.drop('foo').transpose(column_names='bar')
# shape: (1, 4)
# ┌────────────┬────────────┬────────────┬────────────┐
# │ x          ┆ x          ┆ y          ┆ y          │
# │ ---        ┆ ---        ┆ ---        ┆ ---        │
# │ struct[2]  ┆ struct[2]  ┆ struct[2]  ┆ struct[2]  │
# ╞════════════╪════════════╪════════════╪════════════╡
# │ {1,{null}} ┆ {3,{null}} ┆ {5,{null}} ┆ {7,{null}} │
# └────────────┴────────────┴────────────┴────────────┘