These sort of things always seem to assume a fairly relaxed software environment.
In practice I’ve found the big corporates try hard to keep their excel files with financial data and their Python environments with pip & all those associated risks far apart. That’s if pip works at all & isn’t caught by a firewall
Most corporates, last I knew, didn't use Python outside of IT. Devs outside of IT would be using VBA.
However in Financial companies, Python and Excel have always been used together by devs and also quants.
And they tend to use Anaconda, and also like all their other package managers, they would host an in-house package repository and block the public one. That way only approved packages are used, and they only update packages as needed.
Many though have a policy of minimising Excel and rolling out formal platforms whether in-house or off the shelf, as Excel is regarded as a ongoing risk of in-accuracy as full editable at all times, lack of git/version control and so on.
Looking at the content, if you are familiar at all with Python and basic programming, this provides very little new. I sometimes have to stuff massive Excel-abominations with 50k+ rows and rip data I need out of them with Pandas, but it only requires reading Pandas documentation (which is very good) a bit.
But perhaps this might be good if you know no programming and want to make your life easier.
Hey everyone — sharing a tool I've been building that tackles some of these issues in a clean, copy-paste way: https://zither-zeta.vercel.app/
Curious to hear what you think — feedback welcome!
Terrible title. Nothing to do with automating excel. From what I can tell it seems to be about ingesting spreadsheets into panda (and incredibly narrow use of Excel) and working outside of Excel.
In practice I’ve found the big corporates try hard to keep their excel files with financial data and their Python environments with pip & all those associated risks far apart. That’s if pip works at all & isn’t caught by a firewall
However in Financial companies, Python and Excel have always been used together by devs and also quants.
And they tend to use Anaconda, and also like all their other package managers, they would host an in-house package repository and block the public one. That way only approved packages are used, and they only update packages as needed.
Many though have a policy of minimising Excel and rolling out formal platforms whether in-house or off the shelf, as Excel is regarded as a ongoing risk of in-accuracy as full editable at all times, lack of git/version control and so on.
But perhaps this might be good if you know no programming and want to make your life easier.
I've got csv, txt, xlsx in all different shapes and sizes and with just a few settings I can go through them quite easily and very fast as well.