1008 search results for "RStudio"

How does Practical Data Science with R stand out?

June 2, 2014
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How does Practical Data Science with R stand out?

There are a lot of good books on statistics, machine learning, analytics, and R. So it is valid to ask: how does Practical Data Science with R stand out? Why should a data scientist or an aspiring data scientist buy it? We admit, it isn’t the only book we own. Some relevant books from the Related posts:

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Shading between two lines – ggplot

June 1, 2014
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Shading between two lines – ggplot

First one to say geom_ribbon loses. I was plotting some data for a colleague, had two lines (repeated experiment) per person (time on the x axis) facetted by id, I thought it’d be nice to shade the area between the … Continue reading →

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hipsteR: Learn what you missed in R as an early adopter

May 30, 2014
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If you learned R in its early days (say, the early 2000's or even the late 1990's) you may still be using some — ahem — old-fashioned ways to accomplish some tasks better served by newer functions and packages. To help those of us who have may missed some of R's more recent innovations, Karl Broman created hipsteR, a...

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Early Bird Registration for the EARL Conference closes tomorrow (Friday 30th May)

May 29, 2014
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Early Bird Registration for the EARL Conference (Effective Applications of the R Language) closes tomorrow, Friday 30th May. The EARL conference will be held in London on the 15-17th September 2014   EARL is the first cross-sector conference dedicated to the business usage of R and features presentations from over 45 R experts and practitioners.  For further information and to purchase early...

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Early bird registration for R in Insurance ends tomorrow

May 29, 2014
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Early bird registration for R in Insurance ends tomorrow

The early bird registration offer for the 2nd R in Insurance conference, 14 July 2014, at Cass Business School ends tomorrow.This one-day conference will focus once more on applications in insurance and actuarial science that use R, the lingua franca f...

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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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Customising ProjectTemplate in R

May 28, 2014
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This post talks about my workflow for getting started with a new data analysis project using the ProjectTemplate package. Overview of ProjectTemplate ProjectTemplate is an R Package which facilitates data analysis, encourages good data analysis habit...

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Compile times Rcpp11 vs Rcpp

May 22, 2014
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Compile times Rcpp11 vs Rcpp

So I've been curious about a different kind of performance comparison between Rcpp11 and Rcpp, i.e. I've benchmarked the time it takes to compile the following code (the example you get from RStudio when you do new C++ file) with Rcpp and Rcpp11. #...

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The need for documenting functions

May 22, 2014
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The need for documenting functions

My current work usually requires me to work on a project until we can submit a research paper, and then move on to a new project. However, 3-6 months down the road, when the reviews for the paper return, it is quite common to have to do some new analyses or re-analyses of the data.

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dplyr 0.2

May 21, 2014
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dplyr 0.2

I’m very excited to announce dplyr 0.2. It has three big features: improved piping courtesy of the magrittr package a vastly more useful implementation of do() five new verbs: sample_n(), sample_frac(), summarise_each(), mutate_each and glimpse(). These features are described in more detail below. To learn more about the 35 new minor improvements and bug fixes,

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