PDSwR2 Free Excerpt and New Discount Code

Manning has a new discount code and a free excerpt of our book Practical Data Science with R, 2nd Edition: here. This section is elementary, but things really pick up speed as later on (also available in a paid preview). Related To leave a comment for the author, please follow the link and comment on … Read more

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A Shiny app for your perfect circle

Abstract: The perfect circle is a shiny app providing a user friendly interface to the algorithm described in the previous blog post Judging Freehand Circle Drawing Competitions. The app allows one to score freehand circles directly from the mobile by uploading photos of them them to a shiny server. An R package “perfectcircle” contains the … Read more

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Online color apps at hclwizard.org

The hclwizard.org web page has been relaunched, hosting three online color apps based on the HCL (Hue-Chroma-Luminance) color model: a palette constructor, a color vision deficiency emulator, and a color picker. HCL wizard: Somewhere over the rainbow The web page http://hclwizard.org/ had originally been started to accompany the manuscript: “Somewhere over the Rainbow: How to … Read more

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AI, Machine Learning and Data Science Roundup: February 2019

A monthly roundup of news about Artificial Intelligence, Machine Learning and Data Science. This is an eclectic collection of interesting blog posts, software announcements and data applications from Microsoft and elsewhere that I’ve noted over the past month or so. Open Source AI, ML & Data Science News ONNX, the open interchange format for AI … Read more

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Happy Valentines day by Nerds

Real nerds on Valentines day graph hearts instead of drawing them. My drawing skills are not what I like them to be, my R skills are though! Therefore, let’s draw a heart in R instead on paper! dat<- data.frame(t=seq(0, 2*pi, by=0.01) )xhrt<- function(t) 16*sin(t)^3yhrt<- function(t) 13*cos(t)-5*cos(2*t)-2*cos(3*t)-cos(4*t)dat$y=yhrt(dat$t)dat$x=xhrt(dat$t) with(dat, plot(x,y, type=”l”, axes=FALSE, frame.plot=FALSE, labels = FALSE, xlab … Read more

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Roses Are Red, Violets Are Blue, Statistics Can Be Romantic Too!

It’s Valentine’s day, making this the most romantic time of the year. But actually, already 2018 was a year full of love here at STATWORX: many of my STATWORX colleagues got engaged. And so we began to wonder – some fearful, some hopeful – who will be next?Therefore, today we’re going to tackle this question … Read more

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Generate multiple language version plots

The use case is to create the same plot in different languages. I used this technique for Wikipedia plots. We are going to build a list containing all translations, we will then loop over each language, generating and saving the plot. # Mauna Loa atmospheric CO2 change # multi language plot for Wikipedia # Required … Read more

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New discretization method: Recursive information gain ratio maximization

Hello everyone, I’m happy to share a new method to discretize variables I was working on for the last few months: Recursive discretization using gain ratio for multi-class variable tl;dr: funModeling::discretize_rgr(input, target) The problem: Need to convert a numeric variable into one categorical, considering the relationship with the target variable. How do we choose the … Read more

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Try out RStudio Connect on Your Desktop for Free

Have you heard of RStudio Connect, but do not know where to start? Maybe you aretrying to show your manager how Shiny applications can be deployed inproduction, or convince a DevOps engineer that R can fit into her existingtooling. Perhaps you want to explore the functionality of RStudio’s Professionalproducts to see if they fit the … Read more

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In memory of Monty Hall

Some find it a common knowledge, some find it weird. As a professor I usually teach about Monty Hall problem and year after year I see puzzling looks from students regarding the solution. Image taken from http://media.graytvinc.com/images/690*388/mon+tyhall.jpg The original and most simple scenario of the Monty Hall problem is this: You are in a prize … Read more

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So, what is AI really?

One of the topics that is totally hyped at the moment is obviously Artificial Intelligence or AI for short. There are many self-proclaimed experts running around trying to sell you the stuff they have been doing all along under this new label. When you ask them what AI means you will normally get some convoluted … Read more

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German Female Corporate Officers: Where Are You?

Last week, the German NGO Open Knowledge Foundation Deutschland e.V. has made German Trade Resister data available via the project OffeneRegister.de, together with the British NGO opencorporates. In my last blog post I checked the general accessibility of the data. In this quick follow-up post I follow an idea inspired by a tweet by Johannes … Read more

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RFM Analysis in R

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n”,”data”:[[“1″,”2″,”3″,”4″,”5″,”6″,”7″,”8″,”9″,”10″,”11″,”12″,”13″,”14″,”15″,”16″,”17″,”18″,”19″,”20″,”21″,”22″,”23″,”24″,”25″,”26″,”27″,”28″,”29″,”30″,”31″,”32″,”33″,”34″,”35″,”36″,”37″,”38″,”39″,”40″,”41″,”42″,”43″,”44″,”45″,”46″,”47″,”48″,”49″,”50″,”51″,”52″,”53″,”54″,”55″,”56″,”57″,”58″,”59″,”60″,”61″,”62″,”63″,”64″,”65″,”66″,”67″,”68″,”69″,”70″,”71″,”72″,”73″,”74″,”75″,”76″,”77″,”78″,”79″,”80″,”81″,”82″,”83″,”84″,”85″,”86″,”87″,”88″,”89″,”90″,”91″,”92″,”93″,”94″,”95″,”96″,”97″,”98″,”99″,”100″,”101″,”102″,”103″,”104″,”105″,”106″,”107″,”108″,”109″,”110″,”111″,”112″,”113″,”114″,”115″,”116″,”117″,”118″,”119″,”120″,”121″,”122″,”123″,”124″,”125″,”126″,”127″,”128″,”129″,”130″,”131″,”132″,”133″,”134″,”135″,”136″,”137″,”138″,”139″,”140″,”141″,”142″,”143″,”144″,”145″,”146″,”147″,”148″,”149″,”150″,”151″,”152″,”153″,”154″,”155″,”156″,”157″,”158″,”159″,”160″,”161″,”162″,”163″,”164″,”165″,”166″,”167″,”168″,”169″,”170″,”171″,”172″,”173″,”174″,”175″,”176″,”177″,”178″,”179″,”180″,”181″,”182″,”183″,”184″,”185″,”186″,”187″,”188″,”189″,”190″,”191″,”192″,”193″,”194″,”195″,”196″,”197″,”198″,”199″,”200″,”201″,”202″,”203″,”204″,”205″,”206″,”207″,”208″,”209″,”210″,”211″,”212″,”213″,”214″,”215″,”216″,”217″,”218″,”219″,”220″,”221″,”222″,”223″,”224″,”225″,”226″,”227″,”228″,”229″,”230″,”231″,”232″,”233″,”234″,”235″,”236″,”237″,”238″,”239″,”240″,”241″,”242″,”243″,”244″,”245″,”246″,”247″,”248″,”249″,”250″,”251″,”252″,”253″,”254″,”255″,”256″,”257″,”258″,”259″,”260″,”261″,”262″,”263″,”264″,”265″,”266″,”267″,”268″,”269″,”270″,”271″,”272″,”273″,”274″,”275″,”276″,”277″,”278″,”279″,”280″,”281″,”282″,”283″,”284″,”285″,”286″,”287″,”288″,”289″,”290″,”291″,”292″,”293″,”294″,”295″,”296″,”297″,”298″,”299″,”300″,”301″,”302″,”303″,”304″,”305″,”306″,”307″,”308″,”309″,”310″,”311″,”312″,”313″,”314″,”315″,”316″,”317″,”318″,”319″,”320″,”321″,”322″,”323″,”324″,”325″,”326″,”327″,”328″,”329″,”330″,”331″,”332″,”333″,”334″,”335″,”336″,”337″,”338″,”339″,”340″,”341″,”342″,”343″,”344″,”345″,”346″,”347″,”348″,”349″,”350″,”351″,”352″,”353″,”354″,”355″,”356″,”357″,”358″,”359″,”360″,”361″,”362″,”363″,”364″,”365″,”366″,”367″,”368″,”369″,”370″,”371″,”372″,”373″,”374″,”375″,”376″,”377″,”378″,”379″,”380″,”381″,”382″,”383″,”384″,”385″,”386″,”387″,”388″,”389″,”390″,”391″,”392″,”393″,”394″,”395″,”396″,”397″,”398″,”399″,”400″,”401″,”402″,”403″,”404″,”405″,”406″,”407″,”408″,”409″,”410″,”411″,”412″,”413″,”414″,”415″,”416″,”417″,”418″,”419″,”420″,”421″,”422″,”423″,”424″,”425″,”426″,”427″,”428″,”429″,”430″,”431″,”432″,”433″,”434″,”435″,”436″,”437″,”438″,”439″,”440″,”441″,”442″,”443″,”444″,”445″,”446″,”447″,”448″,”449″,”450″,”451″,”452″,”453″,”454″,”455″,”456″,”457″,”458″,”459″,”460″,”461″,”462″,”463″,”464″,”465″,”466″,”467″,”468″,”469″,”470″,”471″,”472″,”473″,”474″,”475″,”476″,”477″,”478″,”479″,”480″,”481″,”482″,”483″,”484″,”485″,”486″,”487″,”488″,”489″,”490″,”491″,”492″,”493″,”494″,”495″,”496″,”497″,”498″,”499″,”500″,”501″,”502″,”503″,”504″,”505″,”506″,”507″,”508″,”509″,”510″,”511″,”512″,”513″,”514″,”515″,”516″,”517″,”518″,”519″,”520″,”521″,”522″,”523″,”524″,”525″,”526″,”527″,”528″,”529″,”530″,”531″,”532″,”533″,”534″,”535″,”536″,”537″,”538″,”539″,”540″,”541″,”542″,”543″,”544″,”545″,”546″,”547″,”548″,”549″,”550″,”551″,”552″,”553″,”554″,”555″,”556″,”557″,”558″,”559″,”560″,”561″,”562″,”563″,”564″,”565″,”566″,”567″,”568″,”569″,”570″,”571″,”572″,”573″,”574″,”575″,”576″,”577″,”578″,”579″,”580″,”581″,”582″,”583″,”584″,”585″,”586″,”587″,”588″,”589″,”590″,”591″,”592″,”593″,”594″,”595″,”596″,”597″,”598″,”599″,”600″,”601″,”602″,”603″,”604″,”605″,”606″,”607″,”608″,”609″,”610″,”611″,”612″,”613″,”614″,”615″,”616″,”617″,”618″,”619″,”620″,”621″,”622″,”623″,”624″,”625″,”626″,”627″,”628″,”629″,”630″,”631″,”632″,”633″,”634″,”635″,”636″,”637″,”638″,”639″,”640″,”641″,”642″,”643″,”644″,”645″,”646″,”647″,”648″,”649″,”650″,”651″,”652″,”653″,”654″,”655″,”656″,”657″,”658″,”659″,”660″,”661″,”662″,”663″,”664″,”665″,”666″,”667″,”668″,”669″,”670″,”671″,”672″,”673″,”674″,”675″,”676″,”677″,”678″,”679″,”680″,”681″,”682″,”683″,”684″,”685″,”686″,”687″,”688″,”689″,”690″,”691″,”692″,”693″,”694″,”695″,”696″,”697″,”698″,”699″,”700″,”701″,”702″,”703″,”704″,”705″,”706″,”707″,”708″,”709″,”710″,”711″,”712″,”713″,”714″,”715″,”716″,”717″,”718″,”719″,”720″,”721″,”722″,”723″,”724″,”725″,”726″,”727″,”728″,”729″,”730″,”731″,”732″,”733″,”734″,”735″,”736″,”737″,”738″,”739″,”740″,”741″,”742″,”743″,”744″,”745″,”746″,”747″,”748″,”749″,”750″,”751″,”752″,”753″,”754″,”755″,”756″,”757″,”758″,”759″,”760″,”761″,”762″,”763″,”764″,”765″,”766″,”767″,”768″,”769″,”770″,”771″,”772″,”773″,”774″,”775″,”776″,”777″,”778″,”779″,”780″,”781″,”782″,”783″,”784″,”785″,”786″,”787″,”788″,”789″,”790″,”791″,”792″,”793″,”794″,”795″,”796″,”797″,”798″,”799″,”800″,”801″,”802″,”803″,”804″,”805″,”806″,”807″,”808″,”809″,”810″,”811″,”812″,”813″,”814″,”815″,”816″,”817″,”818″,”819″,”820″,”821″,”822″,”823″,”824″,”825″,”826″,”827″,”828″,”829″,”830″,”831″,”832″,”833″,”834″,”835″,”836″,”837″,”838″,”839″,”840″,”841″,”842″,”843″,”844″,”845″,”846″,”847″,”848″,”849″,”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O’Reilly DVM”,”Add Senger”,”Aden Lesch Sr.”,”Admiral Senger”,”Agness O’Keefe”,”Aileen Barton”,”Ailene Hermann”,”Aiyanna Bruen PhD”,”Ala Schmidt DDS”,”Alannah Borer”,”Alcide Rohan”,”Aleena Berge”,”Alessandra Heaney”,”Alethea Blanda”,”Alex Armstrong”,”Alex Bergnaum”,”Alexis Cormier”,”Alf Lueilwitz”,”Alferd Ziemann”,”Alfred Metz”,”Almedia Yundt”,”Alpheus Wilkinson”,”Alphonse Champlin V”,”Alton Wintheiser”,”Alvah Bogisich”,”Alvera Balistreri”,”Alwina Wilkinson DDS”,”Alyssia Hickle”,”Amina Renner”,”Amit Langworth”,”Anabel Jakubowski PhD”,”Anastasia Howe”,”Anderson … Read more

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A Look Back on 2018: Part 2

Welcome to the second installment of Reproducible Finance 2019! In the previous post, we looked back on the daily returns for several market sectors in 2018. Today, we’ll continue that theme and look at some summary statistics for 2018, and then extend out to previous years and different ways of visualizing our data. There’s not … Read more

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PlayerIds

Something that has been talked a bit about recently on twitter is the the use of unique playerIDs so that fan analysts, punters and bloggers can track players through time. There are some things that need to be thought about when creating unique playerIDS for analysis. Lets say you are a user of #fitzRoy we … Read more

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Meetup 02-2019 Minutes

Self Service Data Preparation und Data Science Peter Jeitschko Peter presented Alteryx, a platform built for Business Analysts to master tasks like data management, data cleaning and modelling. The tool is windows only and will be ported to Linux soon. It can connect to multiple data sources and helps Business Analysts to deploy models in … Read more

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Community Call Follow-up – Governance of Open Source Research Software Organizations

We tend to know a good open source research software project when we see it: The code is well-documented, users contribute back to the project, the software is licensed and citable, and the community interacts and co-produces in a healthy, productive fashion. The academic literature and community discourse around research software development offer insight into … Read more

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cdata Control Table Keys

In our cdata R package and training materials we emphasize the record-oriented thinking and how to design a transform control table. We now have an additional exciting new feature: control table keys. The user can now control which columns of a cdata control table are the keys, including now using composite keys (that is keys … Read more

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Gabriel and Hugo discuss his role on helping to make the BBC more data informed.

Hugo Bowne-Anderson, the host of DataFramed, the DataCamp podcast, recently interviewed Gabriel Straub, the Head of Data Science and Architecture at the BBC. Here is the podcast link. Hugo: Hi there Gabriel, and welcome to DataFramed. Gabriel: Hello, thanks a lot Hugo for having me. Hugo: Such a pleasure to have you on the show. … Read more

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First post!

You’ll find this post in your _posts directory. Go ahead and edit it and re-build the site to see your changes. You can rebuild the site in many different ways, but the most common way is to run jekyll serve, which launches a web server and auto-regenerates your site when a file is updated. To … Read more

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Direct Optimization of Hyper-Parameter

In the previous post (https://statcompute.wordpress.com/2019/02/03/sobol-sequence-vs-uniform-random-in-hyper-parameter-optimization), it is shown how to identify the optimal hyper-parameter in a General Regression Neural Network by using the Sobol sequence and the uniform random generator respectively through the N-fold cross validation. While the Sobol sequence yields a slightly better performance, outcomes from both approaches are very similar, as shown below … Read more

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A Major Upgrade of the V8 package

This week version 2.0 of the V8 package has been released to CRAN. Go get it now! install.packages(“V8”) The V8 package provides an embedded JavaScript engine that can be used inside of R. You can use it interactively as a JavaScript console, but it is mostly useful for wrapping JavaScript libraries in R packages. Some … Read more

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How did Axios rectangle Trump’s PDF schedule? A try with R

Last week, Axios published a very interesting piece reporting onTrump’s private schedule thanks to an insider’sleak.The headlines all were about Trump’s spending more than 60% of his timein “executive time” which admittedly was indeed the most importantaspect of the story. I, however, also got curious about Axios’ work togo from the PDF schedules to the … Read more

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Multilevel Modelling in R: Analysing Vendor Data

Categories Regression Models Tags Linear Mixed Model Linear Regression R Programming One of the main limitations of regression analysis is when one needs to examine changes in data across several categories. This problem can be resolved by using a multilevel model, i.e. one that varies at more than one level and allows for variation between … Read more

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stringfix : adding transcoder shiny app

Adding quotes to a character list Often I have to take a character list or column and put it in a vector, which means before I have to add quotes. It takes times. For me and my colleagues I have created the transcoder shiny app. The main goal is to facilitate formatting list of strings … Read more

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Manipulating strings with the {stringr} package

{stringr} contains functions to manipulate strings. In Chapter 10, I will teach you about regularexpressions, but the functions contained in {stringr} allow you to already do a lot of work onstrings, without needing to be a regular expression expert. I will discuss the most common string operations: detecting, locating, matching, searching andreplacing, and exctracting/removing strings. … Read more

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Quick Hit: Speeding Up a Slow/Mundane Task with a Little Rcpp

Over at $DAYJOB’s blog I’ve queued up a post that shows how to use our new opendata package to work with our Open Data portal’s API. I’m not super-sure when it’s going to be posted so keep an RSS reader fixed on https://blog.rapid7.com/ if you’re interested in seeing it (I may make a small note … Read more

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Where the German Companies Are

Last week, the German NGO Open Knowledge Foundation Deutschland e.V. has made German Trade Resister data available via the project OffeneRegister.de, together with the British NGO opencorporates. While the data from German Trade Resister is publicly available in principle, retrieving the data is a case-by-case activity and is very cumbersome (try for yourself if you … Read more

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Real Net Profit: 150% in just 4 Months

Developing a post-commission profitable currency trading model using Pivot Billions and R. Needle, meet haystack. Searching for the right combination of features to make a consistent trading model can be quite difficult and takes many, many iterations. By incorporating Pivot Billions and R into my research process, I was able to dramatically improve the efficiency … Read more

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Benchmarking cast in R from long data frame to wide matrix

In my daily work I often have to transform a long table to a wide matrix so accommodate some function. At some stage in my life I came across the reshape2 package, and I have been with that philosophy ever since – I find it makes data wrangling easy and straight forward. I particularly like … Read more

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Deploying an R Shiny App With Docker

If you haven’t heard of Docker, it is a system that allows projects to be split into discrete units (i.e. containers) that each operate within their own virtual environment. Each container has a blueprint written in its Dockerfile that describes all of the operating parameters including operating system and package dependencies/requirements. Docker images are easily … Read more

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NSERC – Discovery Grants Program, over the past 5 years

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 library(XML) library(stringr) url=”http://www.nserc-crsng.gc.ca/NSERC-CRSNG/FundingDecisions-DecisionsFinancement/ResearchGrants-SubventionsDeRecherche/ResultsGSC-ResultatsCSS_eng.asp” download.file(url,destfile = “GSC.html”) library(XML) tables=readHTMLTable(“GSC.html”) GSC=tables[[1]]$V1 GSC=as.character(GSC[-(1:2)]) namesGSC=tables[[1]]$V2 namesGSC=as.character(namesGSC[-(1:2)]) Correction = function(x) as.numeric(gsub(‘[$,]’, ”, x)) YEAR=2013:2018 for(i in 1:length(YEAR)){ … Read more

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Liverpool is the Most Popular City in the World (relative to use as password per inhabitant)

The API of pwnedpasswords.com is quite remarkable. It not only allows you to fetch the results generally obtained by typing in your e-mail into the browser interface and finding out whether or not you’ve been pwned from the comfort of your shell. It further allows you to very simply check whether a certain password has … Read more

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Introducing olsrr

I am pleased to announce the olsrr package, a set of tools for improvedoutput from linear regression models, designed keeping in mindbeginner/intermediate R users. The package includes: comprehensive regression output variable selection procedures heteroskedasticiy, collinearity diagnostics and measures of influence various plots and underlying data If you know how to build models using lm(), you … Read more

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“Correlation is not causation”. So what is?

Machine learning applications have been growing in volume and scope rapidly over the last few years. What’s Causal inference, how is it different than plain good ole’ ML and when should you consider using it? In this report I try giving a short and concrete answer by using an example. Imagine we’re tasked by the … Read more

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Launching codecentric.AI Bootcamp course!

Today, I am happy to announce the launch of our codecentric.AI Bootcamp! This bootcamp is a free online course for everyone who wants to learn hands-on machine learning and AI techniques, from basic algorithms to deep learning, computer vision and NLP. However, the course language is German only, but for every chapter I did, you … Read more

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Create data visualizations like BBC News with the BBC’s R Cookbook

If you’re looking a guide to making publication-ready data visualizations in R, check out the BBC Visual and Data Journalism cookbook for R graphics. Announced in a BBC blog post this week, it provides scripts for making line charts, bar charts, and other visualizations like those below used in the BBC’s data journalism.  The cookbook … Read more

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Statswars

I am stuck at home sick today, so I decided to provide a relational analysis of the Stats Package Wars that have been bubbling away for the past week. True in all its details. If you want something slightly more constructive, consider The Plain Person’s Guide to Plain-Text Social Science. Related To leave a comment … Read more

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Are you leaking h2o? Call plumber!

Create a predictive model with the h2o package. H2o is a fantastic open source machine learning platform with many different algorithms. There is Graphical user interface, a Python interface and an R interface. Suppose you want to create a predictive model, and you are lazy then just run automl. Lets say, we have both train … Read more

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Investigating words distribution with R – Zipf’s law

Hello again! Typically I would start by describing a complicated problem that can be solved using machine or deep learning methods, but today I want to do something different, I want to show you some interesting probabilistic phenomena! Have you heard of Zipf’s law? I hadn’t until recently. Zipf’s law is an empirical law that … Read more

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Le Monde puzzle [#1083]

A Le Monde mathematical puzzle that seems hard to solve without the backup of a computer (and just simple enough to code on a flight to Montpellier): Given the number N=2,019, find a decomposition of N as a sum of non-trivial powers of integers such that (a) the number of integers in the sum is … Read more

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PDSwR2: New Chapters!

We have two new chapters of Practical Data Science with R, Second Edition online and available for review! The newly available chapters cover: Data Engineering And Data Shaping – Explores how to use R to organize or wrangle data into a shape useful for analysis. The chapter covers applying data transforms, data manipulation packages, and … Read more

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Visualizing New York City WiFi Access with K-Means Clustering

Categories Advanced Modeling Tags K Means R Programming Unsupervised Learning Visualization has become a key application of data science in the telecommunications industry. Specifically, telecommunication analysis is highly dependent on the use of geospatial data. This is because telecommunication networks in themselves are geographically dispersed, and analysis of such dispersions can yield valuable insights regarding … Read more

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rstudio::conf 2019 Workshop materials now available

rstudio::conf 2019 featured 15 workshops on tidyverse, Shiny, R Markdown, modeling and machine learning, deep learning, big data, and what they forgot to teach you about working with R. Some of the new workshops for this year touched on topics like putting Shiny applications into production at scale and R & Tensorflow. The conference also … Read more

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R for Quantitative Health Sciences: An Interview with Jarrod Dalton

This interview came about through researching R-based medical applications in preparation for the upcoming R/Medicine conference. When we discovered the impressive number of Shiny-based Risk Calculators developed by the Cleveland Clinic and implemented in public-facing sites, we wanted to learn more about the influence of R Language in the development of statistical science at this … Read more

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R for trial and model-based cost-effectiveness analysis

9 July 2019, University College London Training event (8 July): Torrington (1-19) B07 – Teal Room in Torrington Place, 1-19 (), University College London, United Kingdom Main workshop (9 July): Anatomy G29 J Z Young Lecture Theatre, UCL Medical Sciences and Anatomy (https://goo.gl/maps/biryoFc9CiL2), University College London, United Kingdom. Background and objectives It is our pleasure … Read more

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Ideally, this shouldn’t be happening for such a deep network.

Ideally, this shouldn’t be happening for such a deep network. Related R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more… If you … Read more

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Version 0.7.0 of NIMBLE released

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 0.7.0 provides a variety of new features, as well as various bug fixes. New features include: … Read more

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