2 ms·
I 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 reaso
by dahart 5y ago
I 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 Python. I’m unaware of the state of the Perl ecosystem, does it have something similar?
> how come Perl lags far behind or gets dwarfed in data science by Python?
Perl seems to be lagging behind in general, no? Is there anything specific about data science where Perl should be shining?
- ainiriand 5y agoAlso 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.
- teekert 5y agoAdd in Pandas and Seaborn and you can make some really great visualizations (of categorical data) with a couple of lines of code.
- username223 5y ago> I’m unaware of the state of the Perl ecosystem, does it have something similar [to numpy]? Perl has PDL (http://pdl.perl.org http://pdl.perl.org), which I think predates numpy and does the same kind of array manipulation. As for the original question, Python's dominance for "data science" projects is just a matter of momentum at this point: it's where Google and others have put their money, and that is now affecting undergraduate and graduate courses. Originally, I think it was just that some people didn't like Perl's syntax. Personally, I prefer to use a mix of Perl and Julia, each for its respective strengths, and find Python all-around mediocre.