sparklyr — R interface for Apache Spark

September 27, 2016
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sparklyr — R interface for Apache Spark

We’re excited today to announce sparklyr, a new package that provides an interface between R and Apache Spark. Over the past couple of years we’ve heard time and time again that people want a native dplyr interface to Spark, so we built one! sparklyr also provides interfaces to Spark’s distributed machine learning algorithms and much more. Highlights include: Interactively manipulate Spark data using

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Fitting a distribution in Stan from scratch

September 27, 2016
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Fitting a distribution in Stan from scratch

Last week the French National Institute of Health and Medical Research (Inserm) organised with the Stan Group a training programme on Bayesian Inference with Stan for Pharmacometrics in Paris....

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2016 UK Tour

September 26, 2016
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2016 UK Tour

I'll be in the UK next week doing three talks in three days: First, I'll be giving a talk at the London R-Ladies meetup on Monday October 3rd with...

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DataCamp Course

September 26, 2016
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DataCamp Course

Zachary Deane-Mayer, who collaborates on caret, has put together a DataCamp course on Machine Learning in R. Zach and DataCamp did a great job of developing a course that...

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Quick wordclouds from PubMed abstracts – using PMID lists in R

September 26, 2016
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Quick wordclouds from PubMed abstracts – using PMID lists in R

Wordclouds are one of the most visually straightforward, compelling ways of displaying text info in a graph. Of course, we have a lot of web pages (and even apps) that, given...

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Introduction to BiclustGUI

September 26, 2016
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Introduction to BiclustGUI

BiclustGUI in R Ewoud De Troyer, University of Hasselt (CenStat) Biclustering in a GUI & Growing a GUI together! Introduction We are happy to announce the first release of the BiclustGUI on CRAN...

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A book on RStan in Japanese: Bayesian Statistical Modeling Using Stan and R (Wonderful R, Volume 2)

September 26, 2016
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A book on RStan in Japanese: Bayesian Statistical Modeling Using Stan and R (Wonderful R, Volume 2)

Wonderful, indeed, to have an RStan book in Japanese: Kentarou Matsuura. 2016. Bayesian Statistical Modeling Using Stan and R. Wonderful R Series, Volume 2. Kyoritsu Shuppan Co., Ltd. Google...

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Upgrading to plotly 4.0 (and above)

September 26, 2016
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By Carson Sievert, lead Plotly R developer I’m excited to announce that plotly’s R package just sent its first CRAN update in nearly four months. To install the update,...

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Replicating Plots – Boxplot Exercises

September 26, 2016
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Replicating Plots – Boxplot Exercises

R’s boxplot function has a lot of useful parameters allowing us to change the behaviour and appearance of the boxplot graphs. In this exercise we will try to use...

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Machine Learning for Drug Adverse Event Discovery

September 26, 2016
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Machine Learning for Drug Adverse Event Discovery

We can use unsupervised machine learning to identify which drugs are associated with which adverse events. Specifically, machine learning can help us to create clusters based on gender, age,...

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When Trump visits… tweets from his trip to Mexico

September 25, 2016
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When Trump visits… tweets from his trip to Mexico

I’m sure many of my fellow Mexicans will remember the historically ill-advised (to say the least) decision by our President to invite Donald Trump for a meeting. Talking to some...

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Better Model Selection for Evolving Models

September 25, 2016
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Better Model Selection for Evolving Models

For quite some time now I have been using R’s caret package to choose the model for forecasting time series data. The approach is satisfactory as long as the...

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The biggest liars in US politics

September 25, 2016
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The biggest liars in US politics

Anyone that follows US politics will be aware of the tremendous changes and volatility that has struck the US political landscape in the past year. In this post, I...

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FileTable and storing graphs from Microsoft R Server

September 25, 2016
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FileTable and storing graphs from Microsoft R Server

FileTable has been around now for quite some time and and it is useful  for storing files, documents, pictures and and binary files in a designated SQL Server table...

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Re-introducing Radiant: A shiny interface for R

September 24, 2016
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Radiant is a platform-independent browser-based interface for business analytics in R. I first introduced Radiant through R-bloggers on 5/2/2015 and, according to Dean Attali, the post was reasonably popular....

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tint 0.0.1: Tint Is Not Tufte

September 24, 2016
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tint 0.0.1: Tint Is Not Tufte

A new experimental package is now on the ghrr drat. It is named tint which stands for Tint Is Not Tufte. It provides an alternative for Tufte-style html...

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Surveillance Out of the Box – The #Zombie Experiment

September 24, 2016
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Surveillance Out of the Box – The #Zombie Experiment

Abstract We perform a social experiment to investigate, if zombie related twitter posts can used as a reliable indicator for an early warning system. We show how such a system...

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Windows 10 anniversary updates includes a whole Linux layer – this is good news for data scientists

September 24, 2016
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If you are on Windows 10, no doubt you have heard that Microsoft included the bash shell in its 2016 Windows 10 anniversary update. What you may not know...

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Radial Stacked Area Chart in R using Plotly

September 24, 2016
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In this post we’ll quickly show how to create radial stacked ara charts in plotly. We’ll use the AirPassengers dataset. Inspired by Mike Bostocks post: http://bl.ocks.org/mbostock/3048740 Radial Stacked...

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My first Shiny App: control charts

September 24, 2016
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My first Shiny App: control charts

After having carefully followed the online official Shiny tutorial, I decided to make a quick try at making my very first Shiny App. I should say that I found...

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Environmental Monitoring App

September 23, 2016
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Environmental Monitoring App

Python, R, Qt, peewee, bokeh, pandas, SQLite plus couple of sleepless nights and here you are a сute app for the environmental monitoring needs )))Main window of the application

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Advanced Base Graphics Exercises

September 23, 2016
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Advanced Base Graphics Exercises

Being able to visualize information through plots is essential for a statistic analysis. A simple and clean graph  can explain much more than words.  In this set of exercises you will test...

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Microsoft R at the EARL Conference

September 23, 2016
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Microsoft R at the EARL Conference

Slides have now been posted for many of the talks given at the recent Effective Applications of the R Language (London) conference, and I thought I'd highlight a few...

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A primer on universal function approximation with deep learning (in Torch and R)

September 23, 2016
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A primer on universal function approximation with deep learning (in Torch and R)

Arthur C. Clarke famously stated that “any sufficiently advanced technology is indistinguishable from magic.” No current technology embodies this statement …Continue reading →

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EARL London 2016 revisited – Day 1

September 23, 2016
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EARL London 2016 revisited – Day 1

This year’s EARL conference in London was another huge success. In this blogpost we revisit some of the presentations from Day 1. In stream 1 the conference started off...

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an inverse permutation test

September 22, 2016
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an inverse permutation test

A straightforward but probabilistic riddle this week in the Riddler, which is to find the expected order of integer i when the sequence {1,2,…,n} is partitioned at random into...

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Shiny Server (Pro) 1.4.6

September 22, 2016
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Shiny Server (Pro) 1.4.6

We’ve just released Shiny Server and Shiny Server Pro 1.4.6. Relative to 1.4.2, our previously blogged-about version, the 1.4.6 release primarily includes bug fixes, and mitigations for low-severity security issues found by penetration...

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Size of XDF files using RevoScaleR package

September 22, 2016
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Size of XDF files using RevoScaleR package

It came to my attention that size of XDF (external data frame) file can change drastically based on the compute context and environment. When testing the output of a...

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How to choose the right tool for your data science project

September 22, 2016
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How to choose the right tool for your data science project

by Brandon Rohrer, Principal Data Scientist, Microsoft R or Python? Torch or TensorFlow? (or MXNet or CNTK)? Spark or map-reduce? When we're getting started on a project, the mountain...

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