data scientist 用什么语言 zz

http://www.kdnuggets.com/2013/08/languages-for-analytics-data-mining-data-science.html#!

Top Languages for analytics, data mining, data science

The most popular languages continue to be R (used by 61% of KDnuggets readers), Python (39%), and SQL (37%). SAS is stable at around 20%. The highest growth was for Pig/Hive/Hadoop-based languages, R, and SQL, while Perl, C/C++, and Unix tools declined. We also find a small affinity between R and Python users.

Previous KDnuggets polls looked at high-level Analytics and Data mining software, but sometimes a full-power programming language is needed. That was the focus of the latest KDnuggets Poll, which asked:

What programming/statistics languages you used for an analytics / data mining / data science work in 2013?

Based on a very high response of over 700 voters, the most popular languages continue to be R (now used by 61% of responders), Python (39%), and SQL (37%). On average, there were 2.3 languages used.

For trends, we compared the 2013 results with similar

• 2012 Poll: languages used for analytics / data mining and
• 2011 Poll: languages used for data mining / data analysis?
  

The language with the highest relative growth (2013 vs 2012) was Julia, which doubled in popularity, but still was used only by 0.7% in 2013.

Among more common languages, the largest relative increases in share of usage from 2012 to 2013 were for

• Pig Latin/Hive/other Hadoop-based languages, 19% growth, from 6.7% in 2012 to 8.0% in 2013
• R, 16% growth
• SQL, 14% growth (perhaps the result of increasing number of SQL interfaces to Hadoop and other Big Data systems?)
  

The languages with the largest decline is share of usage were

• Lisp/Clojure, 77% down
• Perl, 50% down
• Ruby, 41% down
• C/C++, 35% down
• Unix shell/awk/sed, 25% down
• Java, 22% down
  

Is there an affinity between R and Python? Yes, people who use R are about 13% more likely to use Python than overall population. Here are the languages more likely to be used with R:

• Julia, 64% more
• Lisp/Clojure, 41% more
• GNU Octave, 27% more
• Pig Latin/Hive/other Hadoop-based languages, 27% more
• Unix shell/awk/sed, 23% more
• Python, 13% more
  

Here are the full results:

What programming/statistics languages you used for an analytics / data mining / data science work in 2013? [713 votes total] % users in 2013    % users in 2012    % users in 2011
R (434 voters in 2013)	60.9% 52.5% 45.1%
Python (277)	38.8% 36.1% 24.6%
SQL (261)	36.6% 32.1% 32.3%
SAS (148)	20.8% 19.7% 21.2%
Java (118)	16.5% 21.2% 24.4%
MATLAB (89)	12.5% 13.1% 14.6%
High-level data mining suite (80)	11.2% not asked in 2012
Unix shell/awk/sed (79)	11.1% 14.7%
C/C++ (66)	9.3% 14.3%
Pig Latin/Hive/other Hadoop-based languages (57)	8.0% 6.7%
Other low-level language (42)	5.9% 11.4%
GNU Octave (40)	5.6% 5.9%
Perl (32)	4.5% 9.0%
Ruby (16)	2.2% 3.8%
Scala (16)	2.2% 2.4%
F# (12)	1.7% not asked in 2012
Lisp/Clojure (7)	1.0% 4.3%
Julia (5)	0.7% 0.3%
None (2)	0.3% 0.7%

Comments
A number of comments, such as one below, pointed that SPSS also has its own language similar to SAS - will include it in the next poll.

Ralph Winters, SPSS Language
It seems odd to exclude SPSS based upon a definition of what is or what is not language. Especially for a language which has such legacy roots, and is backed by IBM. I could argue that both Matlab and R are both not true progamming language, and SAS, as flexible as it is, I would not consider a standarized programming language as well.

Regional participation was

• US/Canada, 50.8%,
• Europe: 25.7%,
• Asia: 11.8%,
• Latin America: 6.7%,
• AU/NZ: 3.2%,
• Africa/Middle East: 1.5%
  

小K 发表于 2013-10-12 09:11
嗯，数数现在用的东西，统计基础的确是学校教的，巩固是工作中学会的，细的分支是工作用到然后看书看paper自 ...

目测，大牛

duanmupeiyi 发表于 2013-10-12 08:07
我会的很多东西都是自学的，包括R LOL

本科必修编程课，打好基础

LOL? 我一定是理解错了什么吧。。

duanmupeiyi 发表于 2013-10-12 08:07
我会的很多东西都是自学的，包括R LOL

本科必修编程课，打好基础

知道你们都比较厉害了啦~~~

最近逛career fair还有一些workshop感觉Hadoop好火

不会hadoop的人泪奔。。。。

上课都会学到吗？？？？

如果只上课，其他啥都不做，you will not do well no matter what field you are in.

Ithink this day and age, ongoing learning is a must for knowledge workers
if you don't like this, you are in the wrong line of work.

sy10017667 发表于 2013-10-11 15:24
上课都会学到吗？？？？

我会的很多东西都是自学的，包括R LOL

本科必修编程课，打好基础
再然后具体需要什么就现学，有时间的话就自己看书，跟跟公开课，网上各种资源都有

知识永远都是不够用的 :P

R Rules lol

嗯，数数现在用的东西，统计基础的确是学校教的，巩固是工作中学会的，细的分支是工作用到然后看书看paper自学的，有的是上班以后的training学的，有的是公开课自学的。比如 machine learning。基础怎么给人讲清楚，是教课当中学会的。
SAS学校教了一点，但是很少，基本需要用的时候都是跟同事学的。基本上，用的很挫。不说了。
R学校只教了很少很少的一点，现在早没人用了。现在用的全部是自学的。
画图什么的，我在学校里的时候R还挫的很。全部后来自学
Py去年刚刚跟udacity and coursera学的，学习记录还在论坛里面有，还跟论坛里面大牛学了不少
sql去年年底刚刚看的coursera
web 什么什么的今年才刚刚沾的，上网看各种教程+问别人
公开课看了一点点mapreduce到底是什么。Pig/Hive那一套，只沾皮毛，工作里面要用，眼巴巴一句句找别人问着学的。过程痛苦的很。还是不太敢说我会mapreduce, hadoop指定不敢说会。

java/c什么的，基本不会。不过迟早得会，才刚刚看了head first的书，处于拿别人的code改改能勉强运行的水平。打算跟udacity java课再过一遍，然后找别人做code review什么的再学一点，可能暂时用来写零星的user defined函数什么的够用了。大系统想都不去想。。。。。。

d3/js，自己弄着玩过。都不知道什么地方会上课教这东西。

药厂biotech的biostatistician我觉得对这些周边东西的要求会较低，如果实在不喜欢我说的这些，还是可以去那种行业。

但是叫什么data scientist, 什么researcher之类的，这些技能逃不过的。

自学也是种技能。。。。。。。不管博士硕士，研究生都读了，掌握提高自己的能力应该是given的。
现在其实条件多好啊，基本网上啥都有了，免费书啊，讨论啊，公开课啊，教程啊，论坛啊，太多了。真的愿意学的，想学不会都难。(conditional on 智力正常)

真是非常非常不肯业余花时间的，也不是说就活不下去。竞争力差也不是就一定没饭吃。不过是风吹草动的时候多些担心而已。其实多少人也就是工作上浑浑噩噩一辈子，混饱肚子，精力用在hobby或者家庭上，that's OK too.

另外其他行业也不见得对自学有这么高的要求，还可以做做非技术工作么。

这讨论跟码农老了是否之前的讨论基本是一样的 ---