Monthly Archives: October 2019

Extracting basic Plots from Novels: Dracula is a Man in a Hole

October 29, 2019
By
Extracting basic Plots from Novels: Dracula is a Man in a Hole

In 1965 the University of Chicago rejected Kurt Vonnegut’s college thesis, which claimed that all stories shared common structures, or “shapes”, including “Man in a Hole”, “Boy gets Girl” and “Cinderella”. Many years later the then already legendary Vonnegut gave a hilarious lecture on this idea – before continuing to read on please watch it … Continue reading "Extracting...

Read more »

(Re)introducing skimr v2 – A year in the life of an open source R project

Theme song: PSA by Jay-Z We announced the testing version of skimr v2 on June 19, 2018. After more than a year of (admittedly intermittent) work, we’re thrilled to be able to say that the package is ready to go to CRAN. So, what happened over the last year? And why are we so excited for v2? Wait, what is a “skimr”? skimr is an R...

Read more »

An Amazon SDK for R!?

October 28, 2019
By

RBloggers|RBloggers-feedburner Intro: For a long time I have found it difficult to appreciate the benefits of “cloud compute” in my R model builds. This was due to my initial lack of understanding and the setting up of R on cloud compute environments. When I noticed that AWS was bringing out a new product AWS Sagemaker, the possiblities of what it could...

Read more »

Sept 2019: “Top 40” New R Packages

October 28, 2019
By
Sept 2019: “Top 40” New R Packages

One hundred and thirteen new packages made it to CRAN in September. Here are my “Top 40” picks in eight categories: Computational Methods, Data, Economics, Machine Learning, Statistics, Time Series, Utilities, and Visualization. Computational Methods eRTG3D v0.6.2: Provides functions to create realistic random trajectories in a 3-D space between two given fixed points (conditional empirical random walks), based on empirical distribution...

Read more »

Mocking is catching

October 28, 2019
By

When writing unit tests for a package, you might find yourself wondering about how to best test the behaviour of your package when the data it’s supposed to munge has this or that quirk, when the operating system is Windows, when a package enhancing its functionality is not there, when a web API returns an error; or you might even wonder how to test...

Read more »

Any one interested in a function to quickly generate data with many predictors?

October 28, 2019
By
Any one interested in a function to quickly generate data with many predictors?

A couple of months ago, I was contacted about the possibility of creating a simple function in simstudy to generate a large dataset that could include possibly 10’s or 100’s of potential predictors and an outcome. In this function, only a subset of the variables would actually be predictors. The idea is to be able to easily generate data...

Read more »

Dogs of New York

October 28, 2019
By
Dogs of New York

The other week I took a few publicly-available datasets that I use for teaching data visualization and bundled them up into an R package called nycdogs. The package has datasets on various aspects of dog ownership in New York City, and amongst other things you can draw maps with it at the zip code level. The package homepage has...

Read more »

Spelunking macOS ‘ScreenTime’ App Usage with R

October 28, 2019
By
Spelunking macOS ‘ScreenTime’ App Usage with R

Apple has brought Screen Time to macOS for some time now and that means it has to store this data somewhere. Thankfully, Sarah Edwards has foraged through the macOS filesystem for us and explained where these bits of knowledge are in her post, Knowledge is Power! Using the macOS/iOS knowledgeC.db Database to Determine Precise User... Continue reading →

Read more »

The Chaos Game: an experiment about fractals, recursivity and creative coding

October 28, 2019
By
The Chaos Game: an experiment about fractals, recursivity and creative coding

Mathematics, rightly viewed, possesses not only truth, but supreme beauty (Bertrand Russell) You have a pentagon defined by its five vertex. Now, follow these steps: Step 0: take a point inside the pentagon (it can be its center if you want to do it easy). Keep this point in a safe place. Step 1: choose … Continue reading The...

Read more »

How to Grow Your Own Data Scientists – a practical guide for the data-driven C-Suite

October 28, 2019
By
How to Grow Your Own Data Scientists – a practical guide for the data-driven C-Suite

Data today is the fuel driving the modern business world. It therefore stands to reason that the ability to read and speak data should be a fairly mainstream skill. Except it isn’t ­- yet. A 2018 report by Qlik suggests that just 24% of business decision were fully confident in their abilities with data. This is despite the fact that, according to...

Read more »

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)