No, you don't have to make a choice. There will be time for each of them!
In our next meetup we'll have two contrasting talks. Andrew Collier, a Data Scientist from South Africa who works at the interface between Academia and Industry, will give the talk "Data Science in the Cloud: Getting Started". Then, Eduard Parsadanyan, a Statistical Programmer from the pharmaceutical industry, will bring the latest updates on "Corporate reporting with R: create and manipulate MS Office documents".
Short contributions and announcements from the audience are always welcome. We want to be a diverse and inclusive group, please come, bring your friends. We're hoping for a nice crowd enjoying interesting talks and chats.
Our generous hosts Hypoport will prepare drinks and snacks for us!
See you there,
p.s. More details on the talks below:
1. Data Science in the Cloud: Getting Started (by Andrew Collier)
Have you ever felt frustrated by your desktop or laptop computer? Too few CPUs? Not enough RAM? In this talk I will show how some of the features of AWS can help you get around these limitations, opening the doors to running bigger jobs more quickly and efficiently.
Does that sound suitable? It will all be directed at running R jobs on AWS. It's also not a sales pitch (I don't work for AWS but I use it all the time!).
2. Corporate reporting with R: create and manipulate MS Office documents (by Eduard Parsadanyan)
R has plenty of ways to create reports. Many of them are nice and fancy; however, in reality, some restrictions may apply. In a corporate world, there is a standard requirement to use MS Office documents such as .docx and .pptx. Even though it is possible, e.g. converting Markdown into a Word document, I have found a better way to create .docx files from R directly.
There is an excellent package called officer and a set of accompanying packages (flextable + rvg + mschart). Good news is that they don't even require an MS Office installation in the system.
During the presentation, I will show how to create a .docx report from a template file and populate it with common elements, such as text, tables, charts, TOC, sections, page headers, and footers.