DataFrame API: allow aggregate functions in `select()`

### Is your feature request related to a problem or challenge?

Be able to run something like this:

```rust
use datafusion::error::Result;
use datafusion::functions_aggregate::expr_fn::approx_distinct;
use datafusion::prelude::*;

#[tokio::main]
async fn main() -> Result<()> {
let ctx = SessionContext::new();

let testdata = datafusion::test_util::arrow_test_data();
ctx.register_csv(
"aggregate_test_100",
format!("{testdata}/csv/aggregate_test_100.csv"),
CsvReadOptions::default().has_header(true),
)
.await?;

ctx.table("aggregate_test_100")
.await?
// Run aggregate in select() without needing to do via aggregate()
.select(vec![
approx_distinct(col("c9")).alias("count_c9"),
approx_distinct(cast(col("c9"), arrow_schema::DataType::Utf8View))
.alias("count_c9_str"),
])?
.show()
.await?;

Ok(())
}
```

Currently failing with:

```
Error: NotImplemented("Physical plan does not support logical expression AggregateFunction(AggregateFunction { func: AggregateUDF { inner: ApproxDistinct { name: \"approx_distinct\", signature: Signature { type_signature: Any(1), volatility: Immutable } } }, params: AggregateFunctionParams { args: [Column(Column { relation: Some(Bare { table: \"aggregate_test_100\" }), name: \"c9\" })], distinct: false, filter: None, order_by: [], null_treatment: None } })")
```

### Describe the solution you'd like

If using aggregate via `select()` then assume no group by.

### Describe alternatives you've considered

_No response_

### Additional context

_No response_