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For me it's SQL and then simply visualizing.


As a bit of background on Mito, it works by passing the parameters from the frontend spreadsheet to the Python kernel backend, which transpiles the spreadsheet formula into Python/Pandas code [0]. So what we're hoping to do down the line is let the user pick which language to translate to, SQL and R being the obvious next steps. But that's a ways away :)

[0] https://trymito.io/blog/transpiler


The problem with SQL is that it is not great with pivoting. But maybe that is not a big problem when you auto-generate the SQL.

I agree, SQL is what I like more for mangling. Except for the pivot/melt part that is




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