Numpy probably.
> Naturally far more efficient
Most data science languages are interpreted with a few higher-level routines. Same with J, for instance - it has adequate performance as well.
Ask HN:Why is Perl so dwarfed in data science by Python?
21–30 of 120 posts
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#22Perl is expressive but the code can be hard to read. In general, Python is readable because it enforces the indentation and other language design choices. Python also got heavyweight libraries such as Numpy and Pandas which put it in the front. Perl do not have have such well known libraries as far as I know.
Add great visualization (Seaborn) and ML (Scikit and numerous frameworks like Pytorch) and you have a pretty complete analytic package.
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#23I'm not a programmer but I did get my start in tech because I installed Mandrake on my computer for fun in the 90s and couldn't figure out how to format the drive back so I could reinstall windows. I was accidentally forced to learn linux, and with that things like bash and Perl. I feel like people who customize their bashrcs and tweaking their IP tables and generally are comfortable scripting, are people who gravitate towards Perl, but for developers and data science folks, Python is much more accessible in terms of finding out how to learn that application of the language to those types of problem? When I thought about learning some more data science a few years ago, the vast majority of the tutorials on youtube etc are for people shifting from apps like excel to things like sql and python, I didn't see anything about Perl.
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#24the bottleneck isn't the machine runing code, it's the people reading the code
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#25It is write only and super hard to read for mere mortals. That alone is probably the main reason. Python is just so much easier to parse for humans.
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#26Perl? What year is this?
(Only half joking, everything is dwarfed by Python in the data science community.)
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#27I love perl for regex scripts, where I need to quickly filter or transform a text file. I never liked it for other kinds of programming projects, for some reason to me it doesn’t feel as well suited to, say, numeric simulations. > Naturally far more efficient What does this mean exactly? One big reason for Python’s success in data science is numpy, which is far more efficient (especially on large data) than vanilla P…
Also data science requires a lot of intermediate/mockup data visualization and python puts matplotlib and scikit-learn right at your fingertips. Hard to find a match Perl side, but I might be wrong.
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#28Is Perl even close to be on a top ten list of languages that make sense for data science? Not to be nasty to the OP, but the question would maybe make sense +10 years ago. Whats baffling now is seeing Perl as a real competitor to anything.
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#29Well, for the longest time perl couldn't distinguish an int from a long when doing computation could be one reason. Perl is just not designed for any kind of math.
Re: Ask HN:Why is Perl so dwarfed in data science by Python?
#30Python got numpy fairly early on. It is fast and powerful.
Then a whole ecosystem was built on top of numpy, with scipy, pandas, PIL, et cetera. Everything that uses n-dimensional arrays used numpy as their base and as a result all those things can be combined trivially. That's very powerful.
Then later came ipython, a much improved interactive shell, and Web based notebooks that are very useful for data science work.
That the language involved is Python isn't even important, imo. Numpy + ecosystem replaced Matlab. All Python has to be is be a better language than Matlab, and it is.