How to calculate row_correlation(linkage disequilibrium matrix) without genotype data?

I want to use the hl.row_correlation() function to get the correlation value (R2) for all SNP pairs in my data.
However, this data is a subset from a public GWAS data, so I don’t have the genotype information for the variants, which is a required feature for the row_correlation function.
Is there any way to calculate the correlation value of multiple SNPs with only RSID, chr, position, n_sample, AF information?

Thanks in advance!

Unfortunately this isn’t possible using only summary data. One thing you might look into is calculating LD from the public thousand genomes or Human Genome Diversity Panel data and using those calculations, but the LD in that dataset won’t be identical to the LD in the dataset where your GWAS was run.