table = pa.table(
    {"user_id": ["abc123", "qrs456"],
     "interaction": [
        {
            "type": "click",
            "element": {'a': "button"},
            "values": [1, 2],
            "structs":[{"foo": "bar"}]},
        {
            "type": "scroll",
            "element": {'a': "window"},
            "values": [3, 4],
            "structs":[{"fizz": "buzz"}]}
     ]
    })

pq.write_table(table, "test_nested_data.parquet")
dataset = ds.dataset("test_nested_data.parquet")

# Select only single field from structs in a list
dataset.to_table(columns={
        "result_name": pc.struct_field(
                pc.list_element(pc.struct_field(ds.field("interaction"), [1]), 
                                ds.scalar(0)), 
                [0])
        }
)
# pyarrow.Table
# result_name: string
# ----
# result_name: [[null,"buzz"]]

# Or keeping struct shape...

struct_subset_type = pa.struct([("structs", pa.list_(pa.struct([("fizz", pa.string())])))])
dataset.to_table(columns={"interaction": ds.field("interaction").cast(struct_subset_type)})
# pyarrow.Table
# interaction: struct<structs: list<item: struct<fizz: string>>>
#   child 0, structs: list<item: struct<fizz: string>>
#       child 0, item: struct<fizz: string>
#           child 0, fizz: string
# ----
# interaction: [
#   -- is_valid: all not null
#   -- child 0 type: list<item: struct<fizz: string>>
# [      -- is_valid: all not null
#       -- child 0 type: string
# [null],      -- is_valid: all not null
#       -- child 0 type: string
# ["buzz"]]]