April 2019

Encryptr now makes it easy to encrypt and decrypt files

April 25, 2019 | 0 Comments

Data security is paramount and encryptr was written to make this easier for non-experts. Columns of data can be encrypted with a couple of lines of R code, and single cells decrypted as required. But what was missing was an easy way to encrypt the file source of that data. ... [Read more...]

Probability of winning a best-of-7-series (part 2)

April 25, 2019 | 0 Comments

In this previous post, I explored the probability that a team wins a best-of-n series, given that its win probability for any one game is some constant . As one commenter pointed out, most sports models consider the home team … Continue reading →
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Meta analysis of multiple multi-omics data… Oy Vey

April 25, 2019 | 0 Comments

TL;DR tidy tibbles can contain non-atomic classes. This is a proof of concept demonstration for such implementation with S4 object-oriented classes, for meta-analysis of complex genomic data. Motivation In my previous post I reviewed the evo...
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How to handle CRAN checks with help from R-hub

April 24, 2019 | 0 Comments

In this post, we shall introduce CRAN checks in general and use the recent changes of the r-devel-linux-x86_64-debian-clang CRAN platform as a case study of how R-hub can help you, package developers, handle CRAN checks and keep up with CRAN platforms. CRAN checks 101 All CRAN packages are R CMD ... [Read more...]

A Few Old Books

April 24, 2019 | 0 Comments

Greg Wilson is a data scientist and professional educator at RStudio. My previous column looked at a few new books about R. In this one, I’d like to explore a few books about programming that people coming from data science backgrounds may not have stumbled upon. The first is ... [Read more...]

Real world tidy interest rate swap pricing

April 24, 2019 | 0 Comments

In this post I will show how easy is to price a portfolio of swaps leveraging the purrr package and given the swap pricing functions that we introduced in a previous post. I will do this in a “real world” environment hence using real market data as per the last 14...
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I walk the (train) line – part trois – Dijkstra’s revenge

April 24, 2019 | 0 Comments

(TL;DR: Author algorithmically confirms what he already knows - that there is a way to get from Newtown Station to a tasty burger. Shortest path from Newtown to tasty burger discovered. Author can’t stop thinking about cheeseburgers. Why didn’t he choose a gym as his destination?)
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A Detailed Guide to the ggplot Scatter Plot in R

April 24, 2019 | 0 Comments

When it comes to data visualization, flashy graphs can be fun. But if you're trying to convey information, especially to a broad audience, flashy isn't always the way to go. Last week I showed how to work with line graphs in R. In this article, I'm going to talk about ...
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Tidy evaluation in R – Simple Examples

April 23, 2019 | 0 Comments

The tidyverse philosophy introduced by Hadley Wickham has been a game changer for the R community. It is based on intuitive rules of what a tidy data set should look like: each variable is a column, each observation is a row (Wickham 2014). At its core, the tidyverse collection of R ...
[Read more...]

Tidy evaluation in R – Simple Examples

April 23, 2019 | 0 Comments

The tidyverse philosophy introduced by Hadley Wickham has been a game changer for the R community. It is based on intuitive rules of what a tidy data set should look like: each variable is a column, each observation is a row (Wickham 2014). At its core, the tidyverse collection of R ...
[Read more...]

How to easily generate a perfectly normal distribution

April 23, 2019 | 0 Comments

Many times, for instance when teaching, I needed to quickly and simply generate a perfectly normally distributed sample to illustrate or show some of its characteristics. This is now very easy to do with the new bayestestR package, which includes the rnorm_perfect function. This function is very similar to ...
[Read more...]

How to easily generate a perfectly normal distribution

April 23, 2019 | 0 Comments

Many times, for instance when teaching, I needed to quickly and simply generate a perfectly normally distributed sample to illustrate or show some of its characteristics. This is now very easy to do with the new bayestestR package, which includes the rnorm_perfect function. This function is very similar to ...
[Read more...]

conditionz: control how many times conditions are thrown

April 23, 2019 | 0 Comments

conditionz is a new (just on CRAN today) R package for controlling how many times conditions are thrown. This package arises from an annoyance in another set of packages I maintain: The brranching package uses the taxize package internally, calling it’s function taxize::tax_name(). The taxize::tax_name() ... [Read more...]

Join, split, and compress PDF files with pdftools

April 23, 2019 | 0 Comments

Last month we released a new version of pdftools and a new companion package qpdf for working with pdf files in R. This release introduces the ability to perform pdf transformations, such as splitting and combining pages from multiple files. Moreover, the pdf_data() function which was introduced in pdftools 2.0 ... [Read more...]

77th Tokyo.R Users Meetup Roundup!

April 23, 2019 | 0 Comments

As the sakura bloomed in Tokyo, another TokyoR User Meetup was held, this time at SONY City! On April 13th useRs from all over Tokyo (and some even from further afield) flocked to Osaki, Tokyo for a special session focused on be... [Read more...]

Probability of winning a best-of-7 series

April 22, 2019 | 0 Comments

The NBA playoffs are in full swing! A total of 16 teams are competing in a playoff-format competition, with the winner of each best-of-7 series moving on to the next round. In each matchup, two teams play 7 basketball games … Continue reading →
[Read more...]

Comparing Point-and-Click Front Ends for R

April 22, 2019 | 0 Comments

Now that I've completed seven detailed reviews of Graphical User Interfaces (GUIs) for R, let's try to compare them. It's easy enough to count their features and plot them, so let's start there. Continue reading →
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