Need to find python function that works like this R func:
proxy::simil(method = "cosine", by_rows = FALSE)
i.e. finds similarity matrix by pair-wise calculating cosine distance between dataframe rows. If NaNs are present, it should drop exact columns with NaNs in these 2 rows
Simil function description (R)
upd. I have also tried to delete NaNs in every pair of rows in loop using cosine func from scipy.spatial.distance. It gives the same result as in R, but works ages :(
You can try this approach: https://github.com/Midnighter/nadist,
alternatively you can use _chk_weights
with nan_screen=True
as described here by metaperture here https://github.com/scipy/scipy/issues/3870, hope that helps.
I have found that Midnighter had posted the same problem previously on stackoverflow: Compute the pairwise distance in scipy with missing values. There are some other solutions there but, as he moved on to cytonize it I bet they were not the best.