Euler Problem 11: Largest Product in a Grid

February 9, 2017
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Euler Problem 11: Largest Product in a Grid

Solution to Euler Problem 11 in the R language. What is the greatest product of four adjacent numbers in the same direction in the 20 by 20 grid? Continue reading → The post Euler Problem 11: Largest Product in a Grid appeared first on The Devil is in the Data.

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RcppArmadillo 0.7.700.0.0

February 8, 2017
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RcppArmadillo 0.7.700.0.0

Time for another update of RcppArmadillo with a new release 0.7.700.0.0 based on a fresh Armadillo 7.700.0. Following my full reverse-dependency check of 318 package (commit of log here), CRAN took another day to check again. Armadillo is a powerful and expressive C++ template library for linear algebra aiming towards a...

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ModernDive: A free introduction to statistics and data science with R

February 8, 2017
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ModernDive: A free introduction to statistics and data science with R

If you're thinking about teaching a course on statistics and data science using R, Chester Ismay and Albert Kim have created an online, open-source textbook for just that purpose. ModernDive is a textbook for that instructs students how to: use R to explore and visualize data; use randomization and simulation to build inferential ideas; effectively create stories using these...

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Twitter sentiment analysis with Machine Learning in R using doc2vec approach

Twitter sentiment analysis with Machine Learning in R using doc2vec approach

Recently I’ve worked with word2vec and doc2vec algorithms that I found interesting from many perspectives. Even though I used them for another purpose, the main thing they were developed for is Text analysis. As I noticed, my 2014 year’s article Twitter sentiment analysis is one of the most popular blog posts on the blog even today. The post

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Reproducible Finance with R: ETF Country Exposure

February 8, 2017
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by Jonathan Regenstein Today, we are going to tackle a project that has long been on my wish list: a Shiny app to take a fund or portfolio, analyze its exposure to different countries, and display those exposures on a world map. Now you know how exciting my wishlists are. Before describing our data importing/wrangling

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R and SQL Server articles

February 8, 2017
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R and SQL Server articles

In past couple of months, I have prepared several articles on R and SQL Server that have been published on SQL Server Central. The idea was, to have couple of articles covering the introduction to R, to basics on R Server, to some practical cases on R with SQL Server. 1) Using Microsoft R in … Continue...

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Data wrangling within the #tidyverse – the design philosophy behind the sjmisc-package #rstats

February 8, 2017
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Data wrangling within the #tidyverse – the design philosophy behind the sjmisc-package #rstats

I’m pleased to announce sjmisc 2.3.0, which was just updated on CRAN. The update might break existing code – however, functions were largely revised to work seamlessly within the tidyverse. In the long run, consistent design makes working with sjmisc more intuitive. Basically, sjmisc covers two domains of functionality: Reading and writing data between R

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Practical Guide to Cluster Analysis in R – Book

February 7, 2017
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Practical Guide to Cluster Analysis in R – Book

Introduction Large amounts of data are collected every day from satellite images, bio-medical, security, marketing, web search, geo-spatial or other automatic equipment. Mining knowledge from these big data far exceeds human’s abilities. Clustering is one of the important data mining methods for...

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Retail customer analytics with SQL Server R Services

February 7, 2017
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Retail customer analytics with SQL Server R Services

In the hyper-competitive retail industry, intelligence about your customers is key. You need to be able to find the right customers, understand what types of customers you have, and know how to keep the best ones. Three solutions based around R and SQL Server R Services will help you do exactly that. To find the right customers, you need...

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A wrapper around nested ifelse

February 7, 2017
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The ifelse function is the way to do vectorised if then else in R. One of the first cool things I learned to do in R a few years back, I got from Norman Matloff’s The Art of R Programming. When you have more than one if then statements, you just nest multiple ifelse functions before you reach the...

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Emily Robinson, from Social Scientist to Data Scientist

February 7, 2017
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Emily Robinson, from Social Scientist to Data Scientist

Maëlle Salmon, a Forwards collaborator, got the chance to interview Emily Robinson, who recently became a data analyst at Etsy. A very inspiring R-Lady! Hi, Emily! Thanks for letting us interview you! You studied Decision Sciences at Rice University and then graduated from INSEAD with a Master’s degree in Management (specialization in Organizational Behavior). What are those fields? How...

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Announcing the release of my e-book: Introduction to Empirical Bayes

February 7, 2017
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Announcing the release of my e-book: Introduction to Empirical Bayes

I’m excited to announce the release of my new e-book: Introduction to Empirical Bayes: Examples from Baseball Statistics, available here. This book is adapted from a series of ten posts on my blog, starting with Understanding the beta distribution a...

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Building Shiny App exercises part 6

February 7, 2017
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Building Shiny App exercises part 6

RENDER FUNCTIONS In the sixth part of our series we will talk about the renderPlot and the renderUI function and then we will be ready to create our first visualization. (Find part 1-5 here). We are going to create a simple interactive scatterplot that will help us see the clusters that are created when we Related exercise sets:

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How to map geospatial data: USA rivers

February 7, 2017
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How to map geospatial data: USA rivers

The post How to map geospatial data: USA rivers appeared first on SHARP SIGHT LABS.

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An Introduction to Spatial Econometrics in R

February 6, 2017
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An Introduction to Spatial Econometrics in R

This tutorial was prepared for the Ninth Annual Midwest Graduate Student Summit on Applied Economics, Regional, and Urban Studies (AERUS) on April 23rd-24th, 2016 at the University of Illinois at Urbana Champaign.

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What Programming Languages Are Used Most on Weekends?

February 6, 2017
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What Programming Languages Are Used Most on Weekends?

Note: Cross-posted with the Stack Overflow blog. Check out the code for this analysis on Kaggle. For me, the weekends are mostly about spending time with my family, reading for leisure, and working on the open-source projects I am involved in. These w...

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Deep Learning in R

February 6, 2017
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Deep Learning in R

  Oksana Kutkina, Stefan Feuerriegel March 7, 2016 Introduction Deep learning is a recent trend in machine learning that models highly non-linear representations of data. In the past years, deep learning has gained a tremendous momentum and prevalence for a variety of applications (Wikipedia 2016a). Among these are image and speech recognition, driverless cars, natural … Continue...

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an accurate variance approximation

February 6, 2017
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an accurate variance approximation

In answering a simple question on X validated about producing Monte Carlo estimates of the variance of estimators of exp(-θ) in a Poisson model, I wanted to illustrate the accuracy of these estimates against the theoretical values. While one case was easy, since the estimator was a Binomial B(n,exp(-θ)) variate ,

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R Tutorial: Visualizing Multivariate Relationships in Large Datasets

February 6, 2017
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R Tutorial: Visualizing Multivariate Relationships in Large Datasets

R Tutorial: Visualizing multivariate relationships in Large Datasets A tutorial by D.M. Wiig In two previous blog posts I discussed some techniques for visualizing relationships involving two or three variables and a large number of cases. In this tutorial I will extend that discussion to show some techniques that can be used on large datasets … Continue...

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In case you missed it: January 2017 roundup

February 6, 2017
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In case you missed them, here are some articles from January of particular interest to R users. The Data Science Virtual Machine on Azure has been updated with the latest Microsoft R Server, and adds RStudio and JuliaPro. A crowdsourced list of local R user groups and community events, maintained by Colin Gillespie. Resources for searching R packages, now...

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Hyetographs, hydrographs and highcharter

February 6, 2017
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Hyetographs, hydrographs and highcharter

Dual y-axes: yes or no? What about if one of them is also reversed, i.e. values increase from the top of the chart to the bottom? Judging by this StackOverflow question, hydrologists are fond of both of these things. It asks whether ggplot2 can be used to generate a “rainfall hyetograph and streamflow hydrograph”, which … Continue...

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How to create a loop to run multiple regression models

February 6, 2017
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How to create a loop to run multiple regression models

A friend asked me whether I can create a loop which will run multiple regression models. She wanted to evaluate the association between 100 dependent variables (outcome) and 100 independent variable (exposure), which means 10,000 regression models. Regression models with multiple dependent (outcome) and independent (exposure) variables are common in genetics. So models will be Related Post

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Live Event: Blogging for Data Scientists

February 6, 2017
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Live Event: Blogging for Data Scientists

This Thursday at 10am I will be doing a live event with John Sonmez, the founder of SimpleProgrammer. The presentation is titled Blogging for Data Scientists. John... The post Live Event: Blogging for Data Scientists appeared first on AriLamstein.com.

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With our powers combined! xgboost and pipelearner

February 6, 2017
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With our powers combined! xgboost and pipelearner

@drsimonj here to show you how to use xgboost (extreme gradient boosting) models in pipelearner.  Why a post on xgboost and pipelearner? xgboost is one of the most powerful machine-learning libraries, so there’s a good reason to use it. pipelearner helps to create machine-learning pipelines that make it easy to do cross-fold validation, hyperparameter grid searching, and more....

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sjPlot-update: b&w-Figures for Print Journals and Package Vignettes #rstats #dataviz

February 6, 2017
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sjPlot-update: b&w-Figures for Print Journals and Package Vignettes #rstats #dataviz

My sjPlot-package was just updated on CRAN with some – as I think – useful new features. First, I have added some vignettes to the package (based on the existing online-documentation) that cover some core features and principles of the sjPlot-package, so you have direct access to these manuals within R. The vignettes are also

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How successful can an R meetup be? meet(R) in Tricity! – RSelenium and Big Data processing

February 6, 2017
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How successful can an R meetup be? meet(R) in Tricity! – RSelenium and Big Data processing

At Thursday (12.01.2017) we had a chance to attend the first TriCity R Users Group (Pomerania, Poland) meeting. The meetup was unexpectedly very successful! The success can be measured in the time attendees spent on ardently comments and questions aft...

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Share your knowledge at EARL 2017 – call for abstracts, San Francisco and London

February 6, 2017
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We invite users and developers of R to submit an abstract for one or more of this year’s EARL Conferences. If you have a real-world business case use of R and you’re proud to share your experience, we want to … Continue reading →

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From a million nested `ifelse`s to the plater package

February 6, 2017
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From a million nested `ifelse`s to the plater package

As a lab scientist, I do almost all of my experiments in microtiter plates. These tools are an efficient means of organizing many parallel experimental conditions. It's not always easy, however, to translate between the physical plate and a useful data structure for analysis. My first attempts to solve this problem--nesting one ifelse call inside of the next...

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My Book is out!

February 6, 2017
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My Book is out!

I am happy to announce that my book about R and Finance (in portuguese) is finally available! The idea of writing a book about R started back in the end of 2015, when I decided to try something different than...

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