Comparison of data analysis packages R, Matlab, Sci. Py, Excel, SAS, SPSS, Stata. Lukas and I were trying to write a succinct comparison of the most popular packages that are typically used for data analysis. I think most people choose one based on what people around them use or what they learn in school, so Ive found it hard to find comparative information. Im posting the table here in hopes of useful comments. Name. Advantages. A PartOfSpeech Tagger POS Tagger is a piece of software that reads text in some language and assigns parts of speech to each word and other token, such as noun. Uploading large files has never been easier Upload files to store them online for instant access and sharing. GigaSize. com allows you to upload large files in just. The TY720 Digital Multimeter is a 4. RMS meter with a 51segment bar graph display. The TY720 multimeter measures Voltage, Current. Disadvantages. Open source Typical users. RLibrary support visualization. Steep learning curve. Yes. Finance Statistics. Matlab. Elegant matrix support visualization. Expensive incomplete statistics support. No. Engineering. Sci. PyNum. PyMatplotlib. Python general purpose programming languageImmature. Yes. Engineering. Excel. Easy visual flexible. 2006 R1 50Th Anniversary Edition For Sale. Large datasets. No. OQlf3kq7dF4/UmFv4B5FQjI/AAAAAAAAFXQ/Aj9tL-MWc6A/s1600/18.PNG' alt='Matlab Portable 2012 Full Size' title='Matlab Portable 2012 Full Size' />Business. SASLarge datasets. Expensive outdated programming language. No. Business Government. Stata. Easy statistical analysis. No. Science. SPSSLike Stata but more expensive and worse70. Matlab Portable 2012 Full Size' title='Matlab Portable 2012 Full Size' />STATCOM Helps to Guarantee a Stable System B. R. Anderson, B. D. Gemmell, C. Horwill, and D. J. Hanson JPE, vol. Improved ZeroCurrent. For two decades, Sequoia Scientific, Inc. Bellevue, WA, has been the worlds only manufacturer of portable, field, and submersible laser particle sizers. The best common practice is to deliver the DCP in a Cru Dataport DX115 hard drive caddy with USB 23 adapter. These hard drive caddys loads directly into a lot of. Bkea0/UekXw4gpa6I/AAAAAAAAAJo/0eKQpVUo0jI/s1600/keyboard-shortcuts-adobe-audition-cs6.jpg' alt='Matlab Portable 2012 Full Size' title='Matlab Portable 2012 Full Size' />SAS, SPSS, and Stata. Theres a bunch more to be said for every cell. Among other things Two big divisions on the table The more programming oriented solutions are R, Matlab, and Python. More analytic solutions are Excel, SAS, Stata, and SPSS. Python immature matplotlib, numpy, and scipy are all separate libraries that dont always get along. Why does matplotlib come with pylab which is supposed to be a unified namespace for everything  Isnt scipy supposed to do that  Why is there duplication between numpy and scipy e. And then theres package compatibility version hell. You can use SAGE or Enthought but neither is standard yet. In terms of functionality and approach, Sci. Py is closest to Matlab, but it feels much less mature. Torrentz domain names are for sale. Send an offer to contactinventoris. International Journal of Engineering Research and Applications IJERA is an open access online peer reviewed international journal that publishes research. Matlabs language is certainly weak. It sometimes doesnt seem to be much more than a scripting language wrapping the matrix libraries. Python is clearly better on most counts. Rs is surprisingly good Scheme derived, smart use of named args, etc. Everyone says SAS is very bad. Matlab is the best for developing new mathematical algorithms. Very popular in machine learning. Ive never used the Matlab Statistical Toolbox. Im wondering, how good is it compared to R Heres an interesting reddit thread on SASStata vs R. SPSS and Stata in the same category they seem to have a similar role so we threw them together. Stata is a lot cheaper than SPSS, people usually seem to like it, and it seems popular for introductory courses. I personally havent used eitherSPSS and Stata for Science weve seen biologists and social scientists use lots of Stata and SPSS. My impression is they get used by people who want the easiest way possible to do the sort of standard statistical analyses that are very orthodox in many academic disciplines. ANOVA, multiple regressions, t and chi squared significance tests, etc. Certain types of scientists, like physicists, computer scientists, and statisticians, often do weirder stuff that doesnt fit into these traditional methods. Another important thing about SAS, from my perspective at least, is that its used mostly by an older crowd. I know dozens of people under 3. SAS.   At that R meetup last week, Jim Porzak asked the audience if there were any recent grad students who had learned R in school. Many hands went up. Then he asked if SAS was even offered as an option. All hands went down. There were boatloads of SAS representatives at that conference and they sure didnt seem to be on the leading edge. But is there ANY package besides SAS that can do analysis for datasets that dont fit into memory  That is, ones that mostly have to stay on disk  And exactly how good as SASs capabilities here anyway If your dataset cant fit on a single hard drive and you need a cluster, none of the above will work. There are a few multi machine data processing frameworks that are somewhat standard e. Hadoop, MPI but Its an open question what the standard distributed data analysis framework will be. Hive Pig  Or quite possibly something else. This was an interesting point at the R meetup. Porzak was talking about how going to My. SQL gets around Rs in memory limitations. But Itamar Rosenn and Bo Cowgill Facebook and Google respectively were talking about multi machine datasets that require cluster computation that R doesnt come close to touching, at least right now. Its just a whole different ballgame with that large a dataset. SAS people complain about poor graphing capabilities. R vs. Matlab visualization support is controversial. One view Ive heard is, Rs visualizations are great for exploratory analysis, but you want something else for very high quality graphs. Matlabs interactive plots are super nice though. Matplotlib follows the Matlab model, which is fine, but is uglier than either IMO. Excel has a far, far larger user base than any of these other options. Thats important to know. I think its underrated by computer scientist sort of people. But it does massively break down at 1. Another option Fortran and CC. They are super fast and memory efficient, but tricky and error prone to code, have to spend lots of time mucking around with IO, and have zero visualization and data management support. Most of the packages listed above run Fortran numeric libraries for the heavy lifting. Another option Mathematica. I get the impression its more for theoretical math, not data analysis. Can anyone prove me wrongGraphicsMagick News. This file was last updated on July 4, 2017. Please note that this file records news for the associated development branch and that each. The Matlab Editor can be accessed programmatically, for a wide variety of possible uses this article shows how. Another option the pre baked data mining packages. The open source ones I know of are Weka and Orange. I hear there are zillions of commercial ones too. Jerome Friedman, a big statistical learning guy, has an interesting complaint that they should focus more on traditional things like significance tests and experimental design. Here the article that inspired this rant. I think knowing where the typical users come from is very informative for what you can expect to see in the softwares capabilities and user community. Id love more information on this for all these options. What do people think Aug 2. Serbo Croatian translation. Apr 2. 01. 5 update Slovenian translation. May 2. 01. 7 update Portugese translation. The Stanford Natural Language Processing Group. About. Mailing lists. Release history. A Part Of Speech Tagger POS Tagger is a piece of software that reads. POS tags like. noun plural. This software is a Java implementation of the log linear part of speech. Kristina Toutanova and Christopher D. Manning. 2. 00. 0. Knowledge Sources Used in a Maximum Entropy Part of Speech Tagger. In. Proceedings of the Joint SIGDAT Conference on Empirical Methods in. Natural Language Processing and Very Large Corpora. EMNLPVLC 2. 00. Kristina Toutanova, Dan Klein, Christopher Manning, and Yoram. Singer. 2. 00. 3. Part of Speech Tagging with a Cyclic. Dependency Network. In Proceedings of HLT NAACL 2. The tagger was originally written by Kristina Toutanova. Since that. time, Dan Klein, Christopher Manning, William Morgan, Anna Rafferty. Michel Galley, and John Bauer have improved its speed, performance, usability, and. The system requires Java 1. Depending on whether. Java and the complexity of the tagger model. MB of memory to run a trained. Plenty of memory is needed. It again depends on the complexity of the model but at. GB is usually needed, often more. Several downloads are available. The basic download contains two trained. English. The full download contains three trained English. Arabic tagger model, a Chinese tagger model. French tagger model, and a. German tagger model. Both versions include the same source and other. The tagger can be retrained on any language, given. POS annotated training text for the language. Part of speech name abbreviations The English taggers use. Penn Treebank tag set. Here are some links to. Penn Treebank English POS tag set. Computational Linguistics article in PDF. Cahills list. See the included README Models. GNU. General Public License v. Source is included. The package includes components for command line invocation, running as a. Java API. code is dual licensed in a similar manner to My. SQL, etc. Open source licensing is under the full GPL. For distributors of. If you dont need a commercial license, but would like to support. For documentation, first take a look at the included. README. txt. Matthew Jockers has kindly produced. This particularly. XML and Mac OS X x. Grid. Galal Aly wrote a. Java with Eclipse. For more details, look at our included javadocs. Maxent. Tagger. There is a brief FAQ. Have a support question Ask us on Stack Overflow. Feedback and bug reports fixes can be sent to our. Recipes. Tag text from a file text. Maxent. Tagger model. File text. txt. output. Format tsv output. File text. tag. We have 3 mailing lists for the Stanford POS Tagger. Java. NLP tools with the exclusion of the parser. Each address is. at lists. This is the best list to post to in order. Java. NLP. users. Please ask support questions on. Stack Overflow using the. You have to subscribe to be able to use this list. Join the list via this webpage or by emailing. Leave the. subject and message body empty. You can also. This list will be used only to announce. Stanford Java. NLP tools. So it will be very low volume expect 1 3. Join the list via this webpage or by emailing. Leave the. subject and message body empty. This list goes only to the software. Its a good address for licensing questions, etc. For. general use and support questions, youre better off joining and using. You cannot join java nlp support, but you can mail questions to. Download basic English Stanford Tagger version 3. MB. Download full Stanford Tagger version 3. MB. The basic download is a 2. MB zipped file with support for. English. The full download is a 1. MB zipped. file, which includes additional English models and trained models. Arabic, Chinese, French, Spanish, and German. In both cases most of the file size is due to the trained model. The only difference between the two downloads is the number. If you unpack the tar file, you should have everything. This software provides a GUI demo, a command line interface. API. Simple scripts are included to invoke the tagger. For more information on use, see the included README. Other models for the Stanford Tagger. Packages for using the Stanford POS tagger from other programming languages by other peopleVersion. Date. Description. Spanish and French UD models. Full. 3. 7. 0. 20. Update for compatibility, German UD model. Full. 3. 6. 0. 20. Updated for compatibility. Full. 3. 5. 2. 20. Updated for compatibility. Full. 3. 5. 1. 20. General bugfixes. Full. 3. 5. 0. 20. Upgrade to Java 8. Full. 3. 4. 1. 20. Add Spanish model. Full. 3. 4. 20. 14 0. French model uses CC tagset. Full. 3. 3. 1. 20. Bugfix release. Full. English model. Full. Full. 3. 1. 5. 20. Full. 3. 1. 4. 20. Improved Chinese model. Full. 3. 1. 3. 20. Minor bug fixes. Full. Included some tech words in the latest model. Full. 3. 1. 1. 20. Caseless models added for English. Full. 3. 1. 0. 20. French tagger added, tagging speed improved. Full. 3. 0. 4. 20. Compatible with other recent Stanford releases. Full. 3. 0. 3. 20. Compatible with other recent Stanford releases. Full. 3. 0. 2. 20. Addition of TSV input format. Full. 3. 0. 1. 20. Faster Arabic and German models. Compatible with other recent Stanford releases. Full. 3. 0. 20. 10 0. Tagger is now re entrant. New tagger objects are loaded with tagger new Maxent. Taggerpath and then used with tagger. Method. English. Full. An order of magnitude faster, slightly more accurate best model. Full. 1. 6. 20. 08 0. A fraction better, a fraction faster, more flexible model specification. Full. 1. 5. 1. 20. Tagger properties are now saved with the tagger, making taggers more portable tagger can be trained off of treebank data or tagged text fixes classpath bugs in 2 June 2. July 2. 00. 8 and packaged with 1. Updated models. 1. Added taggers for several languages, support for reading from and writing to XML, better support for. June 2. 00. 8 to fix a bug with tagging pre tokenized text. Full. 1. 0. 20. 06 0. First cleaned up release after Kristina graduated. Old School. 0. 1.