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In this post I am inspired by two tweets, mainly this one and also this one. Since the total number of articles every year is increasing, no matter which subject you choose, the curve representing number of articles as a function of year of publication... [Read more...]

In this post I am inspired by two tweets, mainly this one and also this one. Since the total number of articles every year is increasing, no matter which subject you choose, the curve representing number of articles as a function of year of publication... [Read more...]

Visualising uncertainty in time-series using animations I was reading an example of visualising election outcome uncertainty using a wobbly needle and wondered, could animating uncertainty help communicate for the kind of work I do on population model... [Read more...]

The Eurovision Song Contest is one of, if not THE biggest international TV song competition in the world. Hundreds of millions of people tune in every year, for stunning voices, weird performances and unforgettable singers. Remember the Epic Sax Guy? He is back again this year! The winner of the ... [Read more...]

Shiny Application Layouts – Dynamic UI In the eightth part of our series we will see how we can build a user interface with dynamically generated components. The UI components are generated on the server side with the use of renderUI() and are displayed with uiOutput() on the ui side. Every ... [Read more...]

Recently I found this guy who create beautiful charts in Tableau. Especially I like this Bump Chart style visualization. I just wondered it can be easy to reproduce it in […] [Read more...]

Abstract In the latest update to the rwml-R Github repo, R code is provided to complete the analysis of New York City taxi data from Chapter 6 of the book “Real-World Machine Learning” by Henrik Brink, Joseph W. Richards, and Mark Fetherolf. Examp... [Read more...]

Last week I posted some analysis of individual voting behaviour in New Zealand’s 2014 general election. In that post, I used logistic regression in four different models to predict the probability of an individual giving party vote to each of the fo... [Read more...]

It's well-known that the home team has an advantage in soccer (or football, as it's called in England). But which teams have made the most of their home-field advantage over the years? Evolutionary biologist (and Liverpool fan) Joe Gallagher analyzed the percentage of points won in the UK Premier League (... [Read more...]

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Shiny Application Layouts – Conditional Panel In the seventh part of our series we will use the rnorm() function to create a UI with a Conditional Panel. This type of Panel is visible only when the value of a JavaScript expression is true. The JS expression is re-evaluated every time shiny ... [Read more...]

XbarR charts are useful when monitoring a continuous process over time and your taking multiple samples in a given period. Some examples might include, the first, middle, and last parts coming off an assembly line, subgroups of molded parts produced several at a time over several cycles, batch uniformity of ... [Read more...]

Following my post about logistic regressions, Ryan got in touch about one bit of building logistic regressions models that I didn’t cover in much detail – interpreting regression coefficients. This post will hopefully help Ryan (and others) out. This was so helpful. Thank you! I'd love to see more about ... [Read more...]

Following my post about logistic regressions, Ryan got in touch about one bit of building logistic regressions models that I didn’t cover in much detail – interpreting regression coefficients. This post will hopefully help Ryan (and others) out. @SteffLocke This was The post How to go about interpreting regression cofficients ... [Read more...]

Focus for books on R tend to be highly focused on either statisticians or programmers. There is a dearth of material to assist those in typically less quantitative field access the powerful tools in the R ecosystem. Enter Text Analysis with R for Students of Literature. I haven't done a ... [Read more...]

R / Finance 2017 starts next Friday, and once again, I am excited about going. It’s true that there are quite a few fun and informative R gatherings these days, but R / Finance is a “big deal” because it is the “real deal”. Finance has been, and remains, one of the ... [Read more...]

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There's a handy new function in R 3.4.0 for anyone interested in data about CRAN packages. It's not documented, but it's pretty simple: tools::CRAN_package_db() returns a data frame with one row for every package on CRAN and 65 columns of data on those packages, as shown below. __ names(tools::... [Read more...]