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This is cool.

I'm a Python engineer (and ML person). I don't use pandas often, so when I do need it, I am constantly on stackoverflow.com and testing single lines at a time in Jupyter.

I'd love a version of Mito where I could give it the original mock table and the desired output table maybe as a function (not using a spreadsheet UI), and it would propose pandas code for me.



This sounds sweet. Pretty much like Excel's auto-fill functionality, but instead it works on entire tables (and generates Pandas code).

I wonder if there are good heuristic-based approaches for determining this. We could always to some ML code-gen, but I prefer deterministic approaches for their reliability (and how it's easy to grok what/why failure occurred) -- at least for now!




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