this post was submitted on 21 Oct 2023
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Technology
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The idea that any scientist is doing data analysis in Excel is honestly terrifying on every level.
You don't want to know...
I remember when a biologist asked us for help - Excel crashed on processing his 700MB tables. Took some time and Chatgpt to convince him to do the analysis in R. It worked out in the end and he is now recommending this solution to his colleagues, which is nice.
Flashback to the time the UK government lost 16,000 positive COVID patients because Excel has a 1 million row limit.
If only there were better ways of storing large amounts of records with a fixed structure. Maybe the future will provide such technology...
And is so bad at it that they can't work around this issue.
Excel is excellent at data analysis... Python integrations and everything
As an alternative, maybe just Python?
Because every scientist is also a programmer?
Especially if they struggle to use Excel properly, no chance.
I’d be embarrassed to call myself a scientist if I didn’t know how to at least script basic shit and effortlessly reproduce data analyses. The bar for entry into every single stage of academic science is too fucking low. 95% of this literature is irreproducible shit, in part because fuckwits don’t know how to code. Scientists don’t need to be software engineers, but yes, they need to be able to program. It wasn’t this way 20 years ago, but it most certainly is nowadays.
Excel sucks open ass. At storing data, at displaying data, at analyzing data. Scientists, of all people, should understand how to use an RDBMS and a data processing framework like R.
I believe that accessibility is what makes Excel so good. And the world agrees.
I’ve seen idiots doing “bioinformatics” with excel & vba. FFS.
What the hell else is there? Good luck getting universities using OpenOffice
Scientists should be using programming languages like R or Python. They are both extremely popular in this field, much more than Excel.
Shoulda coulda. Not everyone is a programmer.
Except every scientist and analyst. Stats, data sci and ML is done in R and Python, be it astro, health data or genomics.
If someone has been taught stats in spreadsheet software, they have have been taught wrong, period.
Also, programming is a very strong term. we're talking about stats in a scripting language, not software development in CPP.
Research projects almost exclusively have more than one person working on them.
They should be if they're doing data analysis like this.
If it works, it works. Programming is a tough thing to learn.
Programming in R or Python isn't a lot harder than learning how to get Excel to do what you want. I'd wager it's easier since you don't have to fight your tools.
Excel has its place for simple quick calculations. But at some point it's simply the wrong tool.