Make your package spherical
Larger packages typically consist of functions that are visible to the users (exported functions) and functions that are used by the exported functions, but that are invisible to the user....continue reading.
Category: R Books
Automated creation of Docker containers
In this blog post, we focus on automated bash/shell scripts to create docker containers. We showcase its usage with an R-shiny example. Der Beitrag Automated creation of Docker containers erschien...continue reading.
Converting Individual Binary Vectors to a Value Based on Column Names
When processing data downloaded from popular survey engines, it’s not uncommon for multiple choice questions to be represented as one column per possible response coded as 0/1. So, a question...continue reading.
Speedmining the Cubing Community with dbplyr
We use the RMariaDB and dbplyr packages to analyze the results database of the World Cubing Association. In particular we are interested in finding unofficial world records of fastest 3x3x3...continue reading.
Making Data part of our organisation’s DNA
Recently, I had the pleasure of co-facilitating a discussion around the obstacles faced by data professionals when it comes to collaborating with other teams in a data context at the...continue reading.
Frankfurt Data Science Meetup: Opening the Black Box
We went to the Frankfurt Data Science Meetup where our Head of Data Science gave a talk about explainable AI. If you missed it, here are the main takeaways! Der...continue reading.
Checking reverse dependencies: the tiny way
The tools package that comes with base R makes checking reverse dependencies super easy. Build your package tarball (the pkg_x.y.z.tar.gz file). R CMD build /your/package/location It is a good idea...continue reading.
R oder Python
Data Science Einsteiger stehen immer wieder vor der gleichen Frage: Welche Programmiersprache sollte man als Erstes lernen? Die Wahl fällt meistens auf eine der beiden großen Anbieter, R oder Python....continue reading.
Summer 2019 workshops: clinical audit stats, and a data science primer for managers
I am doing two BayesCamp workshops in central London this summer: Statistical Analysis for Clinical Audit, 21 June [bookings] Data … Morecontinue reading.
Comparing Point-and-Click Front Ends for R
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...continue reading.
FizzBuzz in R and Python
In this post, we will solve a simple problem (called “FizzBuzz”) that is asked by some employers in data scientist job interviews. The question seeks to ascertain the applicant’s familiarity...continue reading.
A Comparative Review of the JASP Statistical Software
JASP is a free and open source statistics package that targets beginners looking to point-and-click their way through analyses. This article is one of a series of reviews which aim...continue reading.
Data Science Software Used in Journals: Stat Packages Declining (including R), AI/ML Software Growing
In my neverending quest to track The Popularity of Data Science Software, it’s time to update the section on Scholarly Articles. The rapid growth of R could not go on...continue reading.
Data Science Software Reviews: Forrester vs. Gartner
In my previous post, I discussed Gartner’s reviews of data science software companies. In this post, I show Forrester’s coverage and discuss how radically different it is. As usual, this...continue reading.
Call for papers: spatial analysis, agent-based models … Rome, July
I am a co-organiser of the International Workshop on Computational Economics and Econometrics, taking place this year on 3-5 July … Morecontinue reading.
gower 0.2.0 is on CRAN
A new version of R package gower has just been released on CRAN. Thanks to our new contributor David Turner who was kind enough to provide a pull request, gower...continue reading.
How to become a Mango
At Mango, we talk a lot about going on a ‘data-driven journey’ with your business. We’re passionate about data and getting the best use out of it. But for now, instead of...continue reading.
You need to get out more
If you want to pursue a career analysing data about real-world things (and I’m not sure what other data there … Morecontinue reading.
Using parameters in Rmarkdown
Nothing new or original here, just something that I learned about quite recently that may be useful for others. One of my more “popular” code repositories, judging by Twitter, is...continue reading.
ETL – Building a Data Pipeline With Python – Introduction – Part 1 of N
ETL (Extract, Transform, Load) is not always the favorite part of a data scientist’s job but it’s an absolute necessity in the real world. If you don’t understand this process,...continue reading.
