best practices

5 tips to take the Data Science training wheels off

and write more sustainable code.

Dany Majard
7 min readAug 5, 2022

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Photo by David Clarke on Unsplash

Houston, we have a problem

There is a fair amount of snobbery towards wizards of the spreadsheet in the data science community. Yet we are to seasoned ML engineers what excel power users are to us.

Chatting to data scientist at meetups etc, there’s no end to the sarcasm we/they can spit towards excel power users. Who are these cavemen and why do they all have a background in Finance? Why do they think they’re the masters of the universe for their lookup chops, their pivot table addiction, or god forbid their macros??!!

To data scientist, everything they do is painfully convoluted and intrinsically wrong. 😱 when a single tab contains three tables, 😱 when complex lookups perform a simple filtering of a dataset, 😱 when a formula was extended with click and drag but one cell was modified, etc, etc….

To a data scientist, the real world is a jungle of data and spreadsheets are akin to swiss army knifes. You need better tools to survive.

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