1822 search results for "Tutorial"

Visualize Your Foursquare Check-ins with R

May 29, 2014
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Visualize Your Foursquare Check-ins with R

You can use this tutorial in the ThinkToStartR package with: token <-ThinkToStart(“Foursquare_auth”,app_name=”R_Test”,app_id=”XXX”,app_secret=”XXX”) map <- ThinkToStart(“Foursquare_map”,token) Hey R-Fans! You sure all heard of Foursquare. It has more than 45 million users but it´s potential is not recognized by much people. So today I want to show you how easy it is to get your check-in history and visualize …

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R / Finance 2014: Packaged Takeaways

May 29, 2014
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R / Finance 2014: Packaged Takeaways

by Joseph Rickert I was very happy to have been able to attend R / Finance 2014 which wrapped up a couple of weeks ago. In general, the talks were at a very high level of play, some dealing with brand new ideas and many presented at a significant level of technical or mathematical sophistication. Fortunately, most of the...

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Comment sections and help instructions at the Shiny Dev Center

May 28, 2014
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Comment sections and help instructions at the Shiny Dev Center

We’ve added two new features that make it easier to learn Shiny with the Shiny Dev Center. Disqus comments - Each lesson and article on the Dev Center now has its own comments section. Use the comments section to start a discussion or to leave feedback about the articles. How to get help with Shiny –

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Attempt at R version of Peter Norvig’s Spelling Corrector

May 26, 2014
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Attempt at R version of Peter Norvig’s Spelling Corrector

I recently came across a short tutorial by Peter Norvig on natural language processing using some interesting examples. I found it very interesting and really liked Peter Norvig’s explanations and the fact that it was all in ipython notebook for … Continue reading →

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Quick History 2: GLMs, R and large data sets

May 22, 2014
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by Joseph Rickert In last week’s post, I sketched out the history of Generalized Linear Models and their implementations. In this post I’ll attempt to outline how GLM functions evolved in R to handle large data sets. The first function to make it possible to build GLM models with datasets that are too big to fit into memory was...

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R beats Python! R beats Julia! Anyone else wanna challenge R?

May 21, 2014
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R beats Python!  R beats Julia!  Anyone else wanna challenge R?

Before I left for China a few weeks ago, I said my next post would be on our Rth parallel R package. It’s not quite ready yet, so today I’ll post one of the topics I spoke on last night at the Berkeley R Language Beginners Study Group. Thanks to the group for inviting me,

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R beats Python! R beats Julia! Anyone else wanna challenge R?

May 21, 2014
By
R beats Python!  R beats Julia!  Anyone else wanna challenge R?

Before I left for China a few weeks ago, I said my next post would be on our Rth parallel R package. It’s not quite ready yet, so today I’ll post one of the topics I spoke on last night at the Berkeley R Language Beginners Study Group. Thanks to the group for inviting me,

Read more »

Deploying Shiny Server on Amazon: Some Troubleshoots and Solutions

May 18, 2014
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Deploying Shiny Server on Amazon: Some Troubleshoots and Solutions

I really enjoyed Treb Allen‘s tutorial on deploying a Shiny server on an Amazon Cloud Instance. I used this approach for my shiny app that is a map highlighting the economic impact of the recent shale oil and gas boom on the places where the actual extraction happens. The easiest way to proceed is to

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R has some sharp corners

May 15, 2014
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R has some sharp corners

R is definitely our first choice go-to analysis system. In our opinion you really shouldn’t use something else until you have an articulated reason (be it a need for larger data scale, different programming language, better data source integration, or something else). The advantages of R are numerous: Single integrated work environment. Powerful unified scripting/programming Related posts:

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hipsteR: re-educating people who learned R before it was cool

May 15, 2014
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hipsteR: re-educating people who learned R before it was cool

This morning, I started a tutorial for folks whose knowledge of R is (like mine) stuck in 2001. Yesterday I started reading the Rcpp book, and on page 4 there’s an example using the R function replicate, which (a) I’d never heard before, and (b) is super useful. I mean, I often write code like

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