I’m surprised that there aren’t more comments about utilizing R AND Python for analysis work. These two languages actually commingle fairly well, you can build in RStudio if you like that flavor and still import Python packages to use in R code. We do a significant amount of modeling and analysis on large data sets from a variety of disparate sources and utilizing several different packages have extended this out to…
Ditching Excel for Python in a legacy industry
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Re: Ditching Excel for Python in a legacy industry
#112Re: Ditching Excel for Python in a legacy industry
#113I'm a research actuary working in reinsurance. Here is why I think Python creates more problems than it solves from the standpoint of most insurance business users: 1.) Environment management. There are many solutions for managing python dependencies, my favorite is Docker + pip. Good luck getting actuaries and underwriters to write Dockerfiles etc, and good luck getting I.T. to support Docker on Windows desktops. Li…
After a bunch of digging i worked out that the localisation from corporate meant they suddenly had Italian function names not English. Very confusing.
Excel is a program that is both incredible and terrifying to me. There are ways of building spreadsheets that are reliable and auditable. Then there's how 95% of people do it.
You can start out really quickly and make great progress. But it tends to grow and metastasize before you know it.
Re: Ditching Excel for Python in a legacy industry
#114Earlier quoted context omitted.
Absolutely. I worked at Intel and our distributed computing pools went from a combination of SunOS and AIX machines to Linux in about 3 months, essentially overnight, (back in the 90's). It was an astonishingly fast deployment. Linux dominates the server world AND the entertainment device world (hello busybox & gstreamer!) [1] Regarding clunkiness of Python: mostly it is the packages, installation, and 2.x vs 3.x nig…
I think the 2.x vs 3.x issues have mostly been resolved by now. I don't think I've hit one for a long time, and even StackOverflow answers are more likely to be Python 3 now.
but that discounts the tens of thousands of projects that are already out there that are in use and need conversion.
it'll take probably 3-5 years for it to really go away.
Re: Ditching Excel for Python in a legacy industry
#115Earlier quoted context omitted.
It's been a couple years since I've used it, and I didn't feel it was a comparable alternative. It's decent for about 80% of spreadsheet users, but the keyboard shortcuts were lacking and it was missing some functions that I rely on. For keyboard shortcuts, most Excel power users don't use the mouse, so while it sound trivial, it's really hard to feel productive when you have to hunt around for the right button to cl…
> From an enterprise perspective, Excel is so entrenched it would be a 5-10 year effort to port existing spreadsheets to sheets. Practically speaking, most companies wouldn't see the benefit. And at the end of the day, it would have worse performance than Excel both in calculation speed and _much_ worse UI. One of the reasons Excel is so much better than Sheets is speed. Insurance companies spend hundreds of thousand…
Re: Ditching Excel for Python in a legacy industry
#116I'm a research actuary working in reinsurance. Here is why I think Python creates more problems than it solves from the standpoint of most insurance business users: 1.) Environment management. There are many solutions for managing python dependencies, my favorite is Docker + pip. Good luck getting actuaries and underwriters to write Dockerfiles etc, and good luck getting I.T. to support Docker on Windows desktops. Li…
Re: Ditching Excel for Python in a legacy industry
#117Earlier quoted context omitted.
Why doesn't annotating these functions with @functools.lru_cache(10000000) work?
First of all, let me say that I've tried it :) Your recursion needs to "bottom-out" in order for that to work. If you don't get a stack overflow / out of memory error, you're good. But bear in mind that there will be thousands of stack frames. Before you get to time=0 (the recursive base case) in a long-term liability actuarial calc. The recursion isn't simple like the Fibonacci sequence . It's more like: f(t+1) = if…
Re: Ditching Excel for Python in a legacy industry
#118Earlier quoted context omitted.
In Excel there's a toolbar button to toggle showing formulae rather than their results. I realise this doesn't counter your overall objection, but it does mean chasing down logic isn't quite as bad as having to select individual cells one at a time.
I mean... sure? There are a fair number of ways you can mitigate these issues, but the way spreadsheets are structured does not lend itself to structured/ well managed code.
Funny comment in a Python discussion. No type enforcement, no requirement for class/object declarations, circular imports/dependencies allowed, threading/gevent/async messes, variable/class scope weakly enforced
Python is great for a lot of things, but the language is not a beacon of well-managed code. Good Python programmers write nice, easy-to-follow code, just as good Excel builders create very nice, easy-to-follow spreadsheets.
Re: Ditching Excel for Python in a legacy industry
#119I'm pushing for our actuarial team to transition to more R + Git. After 3 years of preaching, most of the actuaries now use RStudio + git as their primary work tool. It is happening. What we did : 1) Provide documentation on everything from install to using internal R libraries for ETL. 2) Provide mostly problem free, always updated VMs with RStudio Server/ Shiny Server. 3) Establish an hotline channel for instant he…
I'm an actuary with a strong interest in this area - would be very interested to hear more especially on your R vs Python experience.
Re: Ditching Excel for Python in a legacy industry
#120Earlier quoted context omitted.
I'm an actuary with a strong interest in this area - would be very interested to hear more especially on your R vs Python experience.
I've used R (3 years) and Python (8+ years) in data science and much prefer Python, because it can do things that aren't just pure data analysis, and because pandas is so amazingly good compared to R's data matrix solutions, in my opinion. I believe that the algorithmic trading industry has gone fully into Python and away from R for these reasons.