R Passes SAS, but Python Leaves Them Both Behind • Hacker News Board

Re: R Passes SAS, but Python Leaves Them Both Behind

#11

Post by nerdponx » Sun, Mar 05, 2017, 5:58 PM UTC

rm999 wrote: post #9

I'm glad to see the quick convergence on Python. I've evaluated Python every ~2 years since 2006 for "data science" tasks (machine learning, statistics, data munging, and visualization). I'd argue that Python only properly covered this full data science stack 1.5-2 years ago. R covered this stack adequately probably around 2011-2012. Matlab had this before 2005. What makes Python a superior language to Matlab and R i…

How do you feel about Julia? Data analysis in Python has plenty of warts.

Re: R Passes SAS, but Python Leaves Them Both Behind

#12

Post by acmj » Sun, Mar 05, 2017, 6:15 PM UTC

nerdponx wrote: post #11

rm999 wrote: post #9

I'm glad to see the quick convergence on Python. I've evaluated Python every ~2 years since 2006 for "data science" tasks (machine learning, statistics, data munging, and visualization). I'd argue that Python only properly covered this full data science stack 1.5-2 years ago. R covered this stack adequately probably around 2011-2012. Matlab had this before 2005. What makes Python a superior language to Matlab and R i…

How do you feel about Julia? Data analysis in Python has plenty of warts.

Julia is great, but IMO, it needs to reach 1.0 first before making a splash. It would be frustrating if you found your tools developed on v0.4 stopped working on v0.5 released a year later. API/ABI stability is critical to the adoption of new programming languages/libraries.

Re: R Passes SAS, but Python Leaves Them Both Behind

#13

Post by fnord123 » Sun, Mar 05, 2017, 6:16 PM UTC

rm999 wrote: post #9

I'm glad to see the quick convergence on Python. I've evaluated Python every ~2 years since 2006 for "data science" tasks (machine learning, statistics, data munging, and visualization). I'd argue that Python only properly covered this full data science stack 1.5-2 years ago. R covered this stack adequately probably around 2011-2012. Matlab had this before 2005. What makes Python a superior language to Matlab and R i…

If you work in a team mixing data engineers and data scientists then python has been a superior choice for a decade as the different team members are all using the same language to build the platform and to use it.

We've had a lot of success weaning people of R and MATLAB in finance (so replace "data scientist" with "quant"). Of course if you work in a field that doesn't have the libraries and can't build them in house then your mileage will certainly vary.

Re: R Passes SAS, but Python Leaves Them Both Behind

#14

Post by blauditore » Sun, Mar 05, 2017, 6:19 PM UTC

I once worked on a piece of software communicating with a SAS instance (doing live decision management), but everything about it seemed sketchy. No one using it really liked it, and its internals always appeared like a blackbox to me. Also, either it is terribly engineered or the devs working with it were just bad - we wanted a JSON-based REST API, but they said that it's "not possible with SAS", so we fell back to badly organized HTTP calls with XML.

Does anybody have some insights about internal quality and code "health" in SAS?

Re: R Passes SAS, but Python Leaves Them Both Behind

#15

Post by Alex3917 » Sun, Mar 05, 2017, 6:33 PM UTC

rm999 wrote: post #9

I'm glad to see the quick convergence on Python. I've evaluated Python every ~2 years since 2006 for "data science" tasks (machine learning, statistics, data munging, and visualization). I'd argue that Python only properly covered this full data science stack 1.5-2 years ago. R covered this stack adequately probably around 2011-2012. Matlab had this before 2005. What makes Python a superior language to Matlab and R i…

> What makes Python a superior language to Matlab and R is the ease of software development.

In practice I think the trends we're seeing have more to do with the fact that most universities now teach CS and data science using Python.

Given that Python is approximately as good as R, and it's becoming increasingly much easier to find good people to hire, there's very little reason not to be a Python shop.

Re: R Passes SAS, but Python Leaves Them Both Behind

#16

Post by chronicx0 » Sun, Mar 05, 2017, 6:44 PM UTC

Alex3917 wrote: post #15

rm999 wrote: post #9

I'm glad to see the quick convergence on Python. I've evaluated Python every ~2 years since 2006 for "data science" tasks (machine learning, statistics, data munging, and visualization). I'd argue that Python only properly covered this full data science stack 1.5-2 years ago. R covered this stack adequately probably around 2011-2012. Matlab had this before 2005. What makes Python a superior language to Matlab and R i…

> What makes Python a superior language to Matlab and R is the ease of software development. In practice I think the trends we're seeing have more to do with the fact that most universities now teach CS and data science using Python. Given that Python is approximately as good as R, and it's becoming increasingly much easier to find good people to hire, there's very little reason not to be a Python shop.

MATLAB requires each function to be its own file. R has terrible object oriented support. Do you seriously think teaching MATLAB or R in universities can save these dying languages?

The only people clinging to R and MATLAB are statisticians and old researchers.

Re: R Passes SAS, but Python Leaves Them Both Behind

#17

Post by Buttons840 » Sun, Mar 05, 2017, 6:48 PM UTC

acmj wrote: post #12

nerdponx wrote: post #11

Earlier quoted context omitted.

How do you feel about Julia? Data analysis in Python has plenty of warts.

Julia is great, but IMO, it needs to reach 1.0 first before making a splash. It would be frustrating if you found your tools developed on v0.4 stopped working on v0.5 released a year later. API/ABI stability is critical to the adoption of new programming languages/libraries.

I've heard they plan to release Julia 1.0 this year. So keep an eye on it.

Re: R Passes SAS, but Python Leaves Them Both Behind

#18

Post by acmj » Sun, Mar 05, 2017, 6:55 PM UTC

Buttons840 wrote: post #17

acmj wrote: post #12

Earlier quoted context omitted.

Julia is great, but IMO, it needs to reach 1.0 first before making a splash. It would be frustrating if you found your tools developed on v0.4 stopped working on v0.5 released a year later. API/ABI stability is critical to the adoption of new programming languages/libraries.

I've heard they plan to release Julia 1.0 this year. So keep an eye on it.

Yeah, I heard about it from others, too. Look forward to it. Hope the dev team stick to the plan.

Re: R Passes SAS, but Python Leaves Them Both Behind

#19

Post by confounded » Sun, Mar 05, 2017, 7:16 PM UTC

This is a sample of non-data-science job postings, which mention buzzwords like "big data".

Java is not a popular language for data analysis.

Re: R Passes SAS, but Python Leaves Them Both Behind

#20

Post by Xcelerate » Sun, Mar 05, 2017, 7:29 PM UTC

I recently finished grad school and accepted a data scientist job a couple weeks ago in part because the job description mentioned expertise with Julia as one of the preferred qualifications (it's rare to see a listing that mentions Julia). It's the language I used for the bulk of my research over the last four years, and has been improving rapidly since it was released. I like Julia a lot more than Python, and I hope it continues rising in popularity. I think once it hits v1.0, we'll begin to see a lot more companies adopting its usage for data science, statistics, and machine learning.