Insight. Applied.
By editor
GlaxoSmithKline (GSK) has reaffirmed it’s commitment to R by joining the R Consortium as a silver member.
Andy Nicholls, Senior Director, Head of Statistical Data Sciences at GSK, said
[R] will help us make better decisions, faster; to the benefit of patients everywhere.
By editor
Imperial College have published their COVID-19 modelling code on GitHub. Their modelling has apparently been used in forming UK policy.
By editor
Interesting, and timely, article on using R to analyse COVID-19 incidence data collated by John Hopkins University.
It makes use of two epidemiology packages.
earlyR for estimation of infectiousness, as measured by the reproduction number (R), in the early stages of an outbreak.
EpiEstim for estimating the time varying instantaneous reproduction number during epidemics
These packages, and many more, are part of the R Epidemics Consortium (RECON). They
[…] gather experts in data science, modelling methodology, public health, and software development to create the next generation of analytics tools for informing the response to disease outbreaks, health emergencies and humanitarian crises, using the R software and other free, open-source resources.
By editor
Andy Kirk at Visualising Data ran a Twitter poll about the relative accessibility of R and Python to non-developers.
59% said that R was more accessible.
Obviously, the poll is far from scientific, but the comments he received reflect my own experiences of teaching both languages—such as the significance of the RStudio IDE and the tidyverse packages in getting people off the ground.
By editor
Jupyter Notebooks are popular with data scientists. Microsoft even offers a free, hosted, “no-install” service for Python, R and F#.
However, there are some downsides to notebooks—mostly to do with software engineering best practices.
Joel Grus gave a provocative talk at JupyterCon 2018 entitled “I Don’t Like Notebooks”. Yihui Xie then followed up with a response to Grus’ talk.
Both authors make a good case and have interesting points. As ever, the truth is that notebooks are good in some situations and not so good in others.
Personally, I use both. Notebooks for smaller, exploratory, data science projects and IDEs (Visual Studio Code, PyCharm and RStudio) for everything else.