1707 search results for "tutorial"

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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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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qqman: an R package for creating Q-Q and manhattan plots from GWAS results

May 15, 2014
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qqman: an R package for creating Q-Q and manhattan plots from GWAS results

Three years ago I wrote a blog post on how to create manhattan plots in R. After hundreds of comments pointing out bugs and other issues, I've finally cleaned up this code and turned it into an R package.The qqman R package is on CRAN: http://cran.r-project.org/web/packages/qqman/The source code is on GitHub: https://github.com/stephenturner/qqmanIf you'd like to cite the...

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Plotly and rOpenSci: Make ggplots shareable and interactive.

May 13, 2014
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Plotly and rOpenSci: Make ggplots shareable and interactive.

By Matt Sundquist Plotly's Co-Founder Here at Plotly, we are on a mission to build a platform where data scientists can analyze data, create beautiful graphs and collaborate: like a GitHub for data, where you can share and find plots, data, and code. The benefits are: Plots (including ggplot2 plots) are interactive and drawn with D3 (try zooming, panning,...

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Cluster your Twitter Data with R and k-means

May 13, 2014
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Cluster your Twitter Data with R and k-means

Hello everbody! Today  I want to show you how you can get deeper insights into your Twitter followers with the help of R. Because I just completed the course “Machine Learning” by Prof. Andrew Ng on Coursera I will use the k-means algorithm and cluster my Twitter followers by the ratio of their followers and how …

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Updated list of upcoming Rcpp talks and workshops

This is an updated version of an earlier post in March. A number of talks about Rcpp are scheduled over the next couple of months: On Wednesday May 14 I will be speaking at the Chicago R Users Group meeting charmingly titled Warm Up for R...

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Enrichment Network

May 10, 2014
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Enrichment Network

Enrichment is beyond random occurrence within a category. Networks can represent relationships among variables. Enrichment networks display relationships among variables which are over represented compared to random chance. Next is  a tutorial for making enrichment networks for biological (metabolomic) data in R using the KEGG database.

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R and Finance

May 8, 2014
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by Joseph Rickert R/Finance 2014 is just about a week away. Over the past four or five years this has become my favorite conference. It is small (300 people this year), exceptionally well-run, and always offers an eclectic mix of theoretical mathematics, efficient, practical computing, industry best practices and trading “street smarts”. This clip of Blair Hull delivering a...

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