Have you ever tried inserting an image into a blogdown post? Maybe you have, or maybe you tried and gave up. Lets first review the hard way before getting to the solution I contributed.
The hard way The process involves copying the target image to the static directory that corresponds to the blogdown post. Lets say that your post is called 2018-03-07-my-new-post.Rmd and lives at content/post/, so it’s full path is content/post/2018-03-07-my-new-post.
This blog post is mostly for myself but maybe it’s useful to others. It contains my current R markdown blog template. I initially posted this as a question at StackOverflow. Then I read how much a burden we put in Yihui Xie and decided that my current setup (copy-pasting) works just fine. In any case using blogdown with the RStudio IDE is much simpler than what I used to do in the past with jekyll or with even my prior setup with blogdown.
As you might know by now, the latest R version was recently released (R 3.4.0). That means that you are highly encouraged to update your R installation. There are several ways to do this some of which are documented in these other blog posts: Tal Galili, 2013, Kris Eberwein, 2015. You would think that it’s just a matter of downloading the latest R installer for your OS, installing it, and continuing your analysis.
tl;dr Please post your question at the Bioconductor support website https://support.bioconductor.org/ and check the posting guide http://www.bioconductor.org/help/support/posting-guide/. It’s important that you provide reproducible code and information about your R session. Recently I have been getting more questions about several packages I maintain. It’s great to see more interest from users, but at the same time most questions lack the information I need to help the users. I have also gotten most of the questions via email, which is why I am writing this post.
Have you ever had to explore a table with data? I believe the answer is yes for most people that work at a computer or even just use it for communicating with their friends and family. Tables of data pop up everywhere, for example in personal finance. Websites like Mint.com allow you to download your transactions in a CSV file called transactions.csv. CSV is one of the many formats for storing tables and most likely when you try to open the transactions.
Over the weekend my brother wanted to figure out his class schedule for the next semester. He is a veterinary medicine and zootechnology student at UNAM. For this upcoming semester there is a set of classes he has to take and each has 8 or so instructor options. The website where he finds the class times lists about 8 pre-constructed class schedules. So he normally finds one he likes quite a bit, and then manually starts checking if he can change X instructor for Y for a given class.
It’s the morning of the first day of oral conferences at #ENAR2016. I feel like I have a spidey sense since I woke up 3 min after an email from Jeff Leek; just a funny coincidence. Anyhow, I promised Valerie Obenchain at #Bioc2014 that I would write a post about one of my favorite Bioconductor packages: BiocParallel (Morgan, Obenchain, Lang, and Thompson, 2016). By now it’s on the top 5% of downloaded Bioconductor packages, so many people know about it or are unaware that their favorite package uses it behind the scenes.
A couple weeks ago I was given the opportunity to teach a 1 hr 30 min slot of an introduction to R course. In the past, I’ve taught lectures for similar courses, and I ended up asking myself what would be the best short topic to teach and how to teach it.
Best short topic There are two ways to answer the first question, one boring and one more interesting.
As a user Imagine that you are starting to learn how to use a specific R package, lets call it foo. You will look at the vignette (if there is one), use help(package = foo), or look at the reference manual (for example, devtools’ ref man). Eventually, you will open the help page for the function(s) you are interested in using.
?function_I_want_to_use In many packages, there is a main use case that is addressed by the package.
This is a guest post by Prasad Patil that answers the question: how to put a shape in the margin of an R plot?
The help page for R’s par() function is a somewhat impenetrable list of abbreviations that allow you to manipulate anything and everything in the plotting device. You may have used this function in the past to create an array of plots (using mfrow or mfcol) or to set margins (mar or mai).