I’ve tried vds.variants_table().to_pandas(expand=False) but it still splits v.
v va.rsid va.qual va.filters va.pass
0 (1, 904165, G, [(G, A)]) . 52346.37  False
1 (1, 909917, G, [(G, A)]) . 1576.94  False
2 (1, 986963, C, [(C, T)]) . 398.06  False
3 (1, 1563691, T, [(T, G)]) . 1090.75  False
Is there a way to get v as chr:start:ref:alt in the dataframe without having to reconstruct it?
As this is the method of choice to uniquely identify a variant, it would make sense to make it available to pandas (as it is to export_variants()).