First. How can i edit with CSS this render?
http://en.wikipedia.org/w/index.php?title=Albert_Einstein&action=render
Second
I have e link http://en.wikipedia.org/w/api.php?action=query&prop=extracts&format=json&exintro=&titles=Stack%20Overflow
RESULT:
{"query":{"pages":{"21721040":{"pageid":21721040,"ns":0,"title":"Stack Overflow","extract":"<p><b>Stack Overflow</b> is a website, the flagship site of the Stack Exchange Network, created in 2008 by Jeff Atwood and Joel Spolsky, as a more open alternative to earlier Q&A sites such as Experts Exchange. The name for the website was chosen by voting in April 2008 by readers of <i>Coding Horror</i>, Atwood's popular programming blog.</p>\n<p>It features questions and answers on a wide range of topics in computer programming. The website serves as a platform for users to ask and answer questions, and, through membership and active participation, to vote questions and answers up or down and edit questions and answers in a fashion similar to a wiki or digg. Users of Stack Overflow can earn reputation points and \"badges\"; for example, a person is awarded 10 reputation points for receiving an \"up\" vote on an answer given to a question, and can receive badges for their valued contributions, which represents a kind of gamification of the traditional Q&A site or forum. All user-generated content is licensed under a Creative Commons Attribute-ShareAlike license.</p>\n<p>As of August 2013<sup class=\"plainlinks noprint asof-tag update\" style=\"display:none;\">[update]</sup>, Stack Overflow has over 1,900,000 registered users and more than 5,500,000 questions. Based on the type of tags assigned to questions, the top eight most discussed topics on the site are: C#, Java, PHP, JavaScript, Android, jQuery, C++ and Python.</p>\n<p></p>"}}}}
How can i give without this and other charachters?
{"query":{"pages":{"21721040":{"pageid":21721040,"ns":0,"title":"Stack Overflow","extract":"
That thing you're getting is a JSON object. I'm not really sure how you're trying to use the data, but you should probably parse that JSON and get only that part which is important to you: extract property.
Ok this question is not exactly technical but very pertinent and current.
If you may have not heard Eureqa (http://creativemachines.cornell.edu/eureqa) is a machine learning (?) based tool that helps you find hidden equations and mathematical relationships within the data. It does sound futuristic and experimental and to a great degree it seems it is.
This is the relevant talk by Eureqa inventor Hod Lipson
http://www.youtube.com/watch?v=Xja6sLl6dVg entitled Mining experimental data.
So i believe this can become popular amongst many R users .
On the official site one can obtain Eureqa clients for MATLAB, Mathematica, Python etc but none so far for R.
So this question is just what it is , is anyone of you working on creating one...or if you know this project do you know what it will take to make one ?
I asked the same question on the Eureqa group a few months ago. Here's the link:
http://groups.google.com/group/eureqa-group/browse_thread/thread/cb251327b50dbd4f
The last entry has the following links:
http://r.eureqa.ivi.eu.com/
http://groups.google.com/group/eureqa-r
I haven't tried this, so I don't know if it works. If you try it, please post your results.
It's very easy to explain NoSQL from high level view - it is basically "key-value" storage. Of course with thousand minor and important things, but in general it's just key value storage.
What's the best way to explain Hadoop and Map/Reduce?
May be some "real world" example which can be easy to give an compare for even newbies? Thanks!
I recently found this great article describing Map Reduce :
I’ve been planning on writing about
the Google’s MapReduce algorithm for
some time but I couldn’t find a good
practical example. Then we had a
Northwest C++ Users Group presentation
by Steve Yegge and a followup
discussion and beers, and I had a
little epiphany. Steve was talking
about, among other things, the build
process. And that’s just a bunch of
algorithms that are perfect for
explaining MapReduce.
The code examples are in C++, but the content is really language agnostic.
Here's a great tutorial on map/reduce in general, explaining the background, basics and data flow. I'm finding it useful to explain Google's App Engine implementation as well.
http://developer.yahoo.com/hadoop/tutorial/module4.html
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I've been using R for a little over a year now and it's been a successful venture. But all too often, I find that there is something that I can't figure out for lack of knowing how to find it or an example of it.
Stackoverflow,
Could you recommend a pathway for learning R in a manner that provides one with a toolset at their disposal to solve problems of a statistical nature?
There's a wealth of knowledge on the internet, between the r-project website and the mailings lists but it seems to be "everywhere" and nowhere when you're actually looking for it.
For example, when I first started using R, I went through "Intro to R". Then I read the language definition (which obviously hasn't sunk in). But every time I ask a question on Stackoverflow I'm presented with some new badass function that is the solution to all my problems in the short term. My question is, how did you know these functions existed in the first place? And how does one go about finding them? Presumably, you read something or found some resources that detoured your learning to the exponential part of the curve. What was it?
Obviously, R's functionality as a statistical tool is broad. For my own purposes I work mostly with economic or financial data. Hence, answers with this in mind would be most helpful.
Completely biased response: learn plyr, reshape2 and ggplot2. They will cover 90% of your data manipulation and visualisation needs. All three packages have a consistent philosophy of data (which the ggplot2 book touches upon), and are designed to be consistent and easier to
learn.
Rather than learning many specialised functions, I really encourage you to learn about simple functions that can be flexibly composed to solve a wide range of problems. This is what plyr strives to do for data manipulation, and what ggplot2 strives to do for visualisation. It does mean you need to invest more time up front to learn a little about the underlying theory, but it's my belief that it will pay off handsomely in the long run.
My way how I learned R.
R resources:
To learn R, the most important resource is google. search for: “TOPIC r-project”, “TOPIC filetype:r”, or “TOPIC site:nabble.com”.
Second, look at the example code provided with most packages. go to “http://bm2.genes.nig.ac.jp/”, search for a topic and look at the example code. run it and adapt it, this way you can often solve part of your problem.
Third: the r-help mailing list. Read the posts, the basic questions get asked over and over again. If you have a problem and you are completely stuck, ask a question on the mailing list.
Finally, look at the source code of the R-packages. that’s the hardest part. if you can alter the code to your needs, you have mastered R ;-)
Some Tips:
R has a steep learing curve. that’s a feature ;-) , it is designed to solve advanced problems and in the end you are fast than when using an alternative to R.
Know every single R package and function that is relevant to your problem. the strength of R is that there are so many packages availiable (around 2000, I think). Usually there is always a package that’s more suited or that already solves your problem. (some help pages are badly written and hard to understand - I got used to it)
R books are not helpful in learning R. yes, that’s true. If you are an expert programmer and expert statistician, you don’t need any book on R. (only exception is Hadley Wickham’s ggplot2 book). If your are not, learn programming in general and/or advanced statistics.
Some R package have known bugs, which nobody will fix (package owner left university, etc.). just a warning, this can be tricky if you are looking for a bug in your code and the bug is in a R package.
I'll start with this:
My question is, how did you know these functions existed in the first place?
Simple - we tried to solve a similar problem and came across that function. It either suited or didn't suit our needs but we now know it's there. I haven't used R much personally but what you're describing is the learning curve for every programming language ever. Firstly, you learn the "grammar" i.e. what you can do. Then you try to do something. You find you can't.
At that stage a programmer has a number of options. What do I do personally? Depends. I'll try and look up that package/header/library/whatever's member functions to see if something suits my needs. I might Google it, because unless you're really pushing the boundaries someone somewhere has probably tried and failed to do it before and had their question answered. If you are pushing the boundaries, someone somewhere has probably tried and failed before, but got no answer. I might try a forum or two to see what happens. I personally don't use IRC much, but that's another option, as are mailing lists depending on how specialised the problem is.
I also have a folder on my computer full of books which I search through depending on the problem and a small library of books I look through/learnt from, which often contain practical, not-quite-there-but-adaptable examples.
My only comment would be attempting to read the language specification is unlikely to be massively useful to you as a beginner. You won't fully understand what it means because you haven't pushed the bounds and tried things yet. For example, a novice in C might try this:
char c = '7';
int x = (int) c;
to convert the character '7' into an integer form. It's not a bad thought process until you understand how characters and ASCII work, then you see why the above doesn't give you what you want.
In short, I think this is going to be part of the learning process and I don't think you can cut it any shorter. The consolation is like any research, the more you do it the more you'll know where to look and what questions to ask on various communities.
One of the things I do is follow the RSS feed of R questions on SO (https://stackoverflow.com/feeds/tag/r). Then I can browse what other people have asked/answered.
Often I will favourite a particular question/answer if I think I'll use it, or jot down the salient points into my notebook software (OneNote), occaisonaly I'll even try the question/answer out myself.
EDIT:
I'd also recomend Patrick Burn's book R-Inferno. It's not so much of a training book as a description of all the gotchas and oooh moments Patrick has found (so far).
There's a free book you might be interested in: Introduction to Probability and Statistics Using R
Here is a good list of resources for learning R:
https://stats.stackexchange.com/questions/138/resources-for-learning-r
Also, that website in general is a good resource.
In general I would say that following a mailing list, or a help list is the best way I have found for learning new things. (That and the "R magazine": http://www.r-bloggers.com )
Learning the RODBC package to interact directly with Oracle data made a big impact at my job. My boss was amazed when I pulled Oracle data directly into R and cranking out a plot in only a few lines of code. Try doing that in Excel!
Moral of the story, learn how to pull in data and manipulate it within R. Then move to some of the cooler stuff like ggplot.
I can recommend Penn University's Introductory Course on R.
The ggplot chapter alone is worth reading - I found ggplot very confusing but this is a great explanation.
The book that helped my learning the most was The Art of R Programming. A lot of programming books can be dry. Since R is commonly an entry point to programming it's important for the voice of materials to resonante with the student. That book did just that with me. The voice felt very casual and I liked that.
Some interesting links:
Intro, links and examples: http://manuals.bioinformatics.ucr.edu/home/programming-in-r
A lot of documentation: https://en.wikibooks.org/wiki/R_Programming
R forum: http://r.789695.n4.nabble.com/
The [R] tag FAQ, right here on Stackoverflow, https://stackoverflow.com/questions/tagged/r?sort=frequent provides numerous reproducible examples that one can use to "learn by doing".
Most of the problems are very common and will eventually be something that you will have to look up as a beginner. The FAQ also provides highly literate (and experienced) examples of usage for a diverse range of functions and useful packages.
If you're new to R, and you prefer a more hands on approach to learning, the FAQ should not be overlooked as a potential resource for learning. Many of the questions also provide useful discussion surrounding paradigms of the language itself (vectorization, workflow, debugging are just a few examples).
Nearly every question in the FAQ is worth studying as a new user as it touches on elements that, speaking for myself, I wish I had been pointed to when I asked this question originally.
Just a few examples:
How to make a great R reproducible example
Grouping functions (tapply, by, aggregate) and the *apply family
Workflow for statistical analysis and report writing
How to sort a dataframe by multiple column(s)?
What is your favorite R debugging trick?
I’m trying to find some objective comparisons of Captaris and K2 workflow products. I haven’t been able to find anything through the usual channels so if anyone out there has an understanding of both products I’d really like to hear from you. I’m primarily interested in the pros and cons of each for use with ASP.NET and also with SharePoint. Thanks.
You're in for a good fight Troy :)
A couple years ago I was trying to answer the same question but we had Ultimus as the main option. At the time I found an even older PDF file with a few info (http://www.scribd.com/doc/6910318/DOt-Net-FAQ24) but we ended up getting their sales reps to give formal presentations.
We ended up with Ultimus for that project, but a few months later I saw a presentation from Nintex and it was interesting too, even tho the project related to it did not came thru.
For the sake of actually completing this question and providing an answer, there are no comparisons! At best there are several mentions of the two in the same sentence but these are many years old and certainly don’t rate as objective comparisons. Captaris is also now OpenText Workflow Server.