[aldanor]

Could you give a hint of how the data ("sample1", "sample2") looks like, or how to randomly generate it in order to benchmark it sensibly? I guess these are similarly-indexed float64 series where the index may contain duplicates? Maybe you could share a chunk of data (as input to genetic_distance() function) as an example if it's not too proprietary and if it's sufficient to run a micro benchmark.

There's also code in genetic_distance() function that IIUC is meant to handle the case when sample1 and sample2 are not similarly-indexed, however (a) you essentially never use it, since you only pass sample1 and sample2 that are columns of the same dataframe (what's the point then?), and (b) your code would actually throw an exception if you tried doing that.

P.S. I like the part where you've removed the comment "note that this is a slow computation" :)