Font size of code in .Rpres presentations
I don’t know if I even knew about the .Rpres presentation feature in RStudio v. 0.98 and above. As I think I mentioned I’ve been rather ill for the last couple of years and I’m afraid I kind of fell out of touch with things a bit. Anyway, I’m all better now and I’m going to be giving a talk at the R User Group in Nottingham (which I love profoundly) so I thought I’d do it this new sexy way.
Better Git commit messages
Something else I’m trying to be better at is using Git. I did use it, briefly, a few years back but I never quite got the hang of it and I’ve reverted to the bad habit of having MainCode/ and TestingCode/ and TryNewFunction/ folders filled with near identical code. So I’m back on the Git wagon again. Atom (see my previous blog post) has beautiful Git integration, as you’d expect since it was built by the GitHub people.
Ellen Townsend: Small talk saves lives — IMH Blog (Nottingham)
It sounds much too simple doesn’t it? Making small talk could save a life. But the truth is, it really could. Today SHRG is supporting the campaign launched by the Samaritans. They are asking us all to be courageous and strike up a conversation with someone if we are worried about them at a railway […] via Ellen Townsend: Small talk saves lives — IMH Blog (Nottingham)
Filtering data straight into a plot with tidyverse
I’m still trying to go full tidyverse, as I believe I mentioned a while back. It’s clearly a highly useful approach, but on top of this I see a load of code in blogs and tutorials that uses a tidy approach. So unless I learn it I’m not going to have a lot of luck reading it. I saw somebody do the following a little while back and I really like it so I thought I’d share it.
One editor to rule them all- Atom
I’m very happy using RStudio for all my R code. It goes without saying that the support for R coding built into RStudio is phenomenal. If you don’t know loads of cool stuff RStudio does, you’re missing out, but that’s a blog post on its own. I’ve never quite been happy with my choice for other general editing, though. Sometimes I write PHP, HTML, markdown, Python, or something else, and I’ve never really found an editor that I love.
Lazy tables with R and pander
One of the many things I love about R is how gloriously lazy it can help you to be. I’m writing a report at the moment and I need to make lots of tables in R Markdown. I need them to be proportions, expressed as a percentage, rounded to 0 decimal places, and I need to add (%) to each label on the table. That’s a lot of code when you’ve got 8 or 10 tables to draw, so I just made a function that does it.
Quarters and modulo arithmetic
This is another post that’s mainly for my benefit when I inevitably forget. I’m working with dates in PHP which, unlike MySQL, does not have a built in quarter function for extracting the quarter from a year. Even if it did, one would have to be very careful with it because quarters are actually defined differently in different countries. In the UK, where I am, April to June is the first quarter (and January to March the last).
Consuming REST APIs with PHP and CURL
I wasted such a lot of time on this that I must commit it to the internet on the off chance that it helps someone else in the same situation. If you are using PHP to consume a RESTful API via CURL and you want to manipulate the data you get back it’s very important that you set CURLOPT_RETURNTRANSFER to true. This allows you to collect the response from the server in a variable.
Converting a grouped plyr::ddply() to dplyr
I’m going full tidyverse at the moment and so I’m converting my old plyr code to dplyr. It’s been pretty steady going so far, although I had a bit of difficulty converting an instruction using ddply which carried out a function based on a subgrouping within the data. I wrote a toy example to get it right, I may as well share it with the internet in case it helps someone else.
Munging Patient Opinion data with R
I’ve written a post about using Patient Opinion’s new API, focusing on how to download your data using R but also perhaps useful to those using other languages as a gentle introduction, which can be found here. This post focuses on the specific data operations which I perform in R in order to get the data nicely formatted and stored on our server. This may be of interest to those using R who want to do something very similar, much of this code will probably work in a similar context.