Consider adding a parameter to nest aggregated columns: aggregate(under: String?)

```
df.groupBy { key }.aggregate {
1 into "col"
}
```
schema:
```
key
col
```

```
df.groupBy { key }.aggregate(under = "statistics") {
1 into "col"
}
```
schema:
```
key
statistics:
col
```

Make sure it's consistent across other aggregate overloads (if makes sense)