1983 search results for "Rstudio"

How many calories should you eat per day?

July 6, 2016
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How many calories should you eat per day?

How many calories should you eat per day, based on your age, sex, and activity level? Here are the US government's recommendations. The post How many calories should you eat per day? appeared first on Decision Science News.

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tibble 1.1

July 5, 2016
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tibble 1.1

We’re proud to announce version 1.1 of the tibble package. Tibbles are a modern reimagining of the data frame, keeping what time has shown to be effective, and throwing out what is not. Grab the latest version with: install.packages("tibble") There are three major new features: A more consistent naming scheme Changes to how columns are

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httr 1.2.0

July 5, 2016
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httr 1.2.0

httr 1.2.0 is now available on CRAN. The httr package makes it easy to talk to web APIs from R. Learn more in the quick start vignette. Install the latest version with: install.packages("httr") There are a few small new features: New RETRY() function allows you to retry a request multiple times until it succeeds, if

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xml2 1.0.0

July 5, 2016
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xml2 1.0.0

We are pleased to announced that xml2 1.0.0 is now available on CRAN. Xml2 is a wrapper around the comprehensive libxml2 C library, and makes it easy to work with XML and HTML files in R. Install the latest version with: install.packages("xml2") There are three major improvements in 1.0.0: You can now modify and create

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A Simple Prediction Web Service Using the New fiery Package

July 5, 2016
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fiery is a new Rook/httuv-based R web server in town created by @thomasp85 that aims to fill the gap between raw http & websockets and Shiny with a flexible framework for handling requests and serving up responses. The intent of this post is to provide a quick-start to using it setup a prediction API service.... Continue reading →

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Euro 2016 analytics: Who’s playing the toughest game?

July 1, 2016
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Euro 2016 analytics: Who’s playing the toughest game?

I am really enjoying Uefa Euro 2016 Footbal Competition, even because our national team has done pretty well so far. That’s why after  browsing for a while statistics section of official EURO 2016 website I decided to do some analysis on the data they share Just to be clear from the beginning: we are not talking Related Post

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RMarkdown and Metropolis/Mtheme

June 30, 2016
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Nick Tierney asked on Twitter about rmarkdown and metropolis about whether folks had used RMarkdown-driven LaTeX Beamer presentations. And the answer is a firm hell yeah. I have been using mtheme (and/or a local variant I called 'm2') as well as the ...

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The useR! 2016 Tutorials

June 30, 2016
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by Joseph Rickert Over the years I have seen several excellent tutorials at useR!conferences that were not only very satisfying "you had to be there" experiences but were also backed up with meticulously prepared materials of lasting value. This year, quite a few useR!20i6 tutorials measure up to this level of quality. My take on why things turned out...

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Express Intro to dplyr

June 28, 2016
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Express Intro to dplyr

Working The Data Like a Boss ! I recently introduced the data.table package which provides a nice way to manage and aggregate large data sources using the standard bracket notation that is commonly employed when manipulating data frames in R. As data sources grow larger one must be prepared with a variety of approaches to

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Making “Time Rivers” in R

June 28, 2016
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Making “Time Rivers” in R

Once again, @albertocairo notices an interesting chart and spurs pondering in the visualization community with his post covering an unusual “vertical time series” chart produced for the print version of the NYTimes: I’m actually less concerned about the vertical time series chart component here since I agree with TAVE* Cairo that folks are smart enough... Continue reading →

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