Hi, with a 2-D ndsparse table (with one value column), I am trying to select the max value for each of the 1st dimension of the index, but I am not really sure how to do that (groupby removes the second dimension, which I need to keep). For example, with a table like this:

```
2-d NDSparse with 8 values (Float64):
a b │
─────┼──────────
1 1 │ 0.196028
1 2 │ 0.0369555
1 3 │ 0.630628
2 4 │ 0.521345
2 5 │ 0.495389
2 6 │ 0.300472
3 7 │ 0.212149
3 8 │ 0.816977
```

I would like to produce the following:

```
2-d NDSparse with 8 values (Float64):
a b │
─────┼──────────
1 3 │ 0.630628
2 4 │ 0.521345
3 8 │ 0.816977
```

In pandas, you can usually filter out duplicates based on one index of a multi-indexed dataframe, but I’m not sure how to closely approximate that here.

Thank you!