These levels have been defined by the software carpentry people, and I have modified them to this:

  • beginner: You have just started out in this topic. You do not yet know how things are supposed to work. You do not have a mental model of this thing
  • intermediate: You are a regular user of this software/tool/concept, you have a mental model, but it is not very sophisticated
  • advanced: You have a sophisticated mental model how things work, and you even know when the model breaks, when it does not match reality.

Building the oomsifyer

Today I will show you a quick hack (OK it took me like 4 hours during my travels today yesterday and today), on how to add a dancing banana to any picture. Now, you might be thinking… Really, why would you add a dancing banana to a picture, but I don’t have time for that kind of negativity in my life. Why oomsifier? Jeroen Ooms is one of those crazy productive people in the R world. [Read More]

Where to live in the Netherlands based on temperature XKCD style

After seeing a plot of best places to live in Spain and the USA based on the weather, I had to chime in and do the same thing for the Netherlands. The idea is simple, determine where you want to live based on your temperature preferences. First the end result: This post explains how to make the plot, to see where I got the data and what procedures I took look at https://github. [Read More]

Writing manuscripts in Rstudio, easy citations

Intro and setup This is a simple explanation of how to write a manuscript in RStudio. Writing a manuscript in RStudio is not ideal, but it has gotten better over time. It is now relatively easy to add citations to documents in RStudio. **The goal is not think about formatting, and citations, but to write the manuscript and add citations on the fly with a nice visual help. ** This tutorial explains how to link Zotero (a reference manager) to your project folder and how to easily add citations. [Read More]

Plotting a map with ggplot2, color by tile

Introduction Last week I was playing with creating maps using R and GGPLOT2. As I was learning I realized information about creating maps in ggplot is scattered over the internet. So here I combine all that knowledge. So if something is absolutely wrong/ ridiculous / stupid / slightly off or not clear, contact me or open an issue on the github page. When you search for plotting examples you will often encounter the packages maps and mapdata. [Read More]

Submitting your first package to CRAN, my experience

I recently published my first R package to The Comprehensive R Archive Network (CRAN). It was very exciting and also quite easy. Let me walk you through my process. First a description of my brand new package: badgecreatr, then a description of steps to take for submission. Package description When you go around github looking at projects you often see these interesting images in the readme The ones you see above are from ggplot2. [Read More]

Your most valuable collaborator, future-you

You don’t want future-you to curse past-you

I was recently at a R users meetup where Hadley Wickham talked about data wrangling. He showed some interesting stuff! Did you know that you can put a data frame into a data frame? You can make a list of data frames and add that list to your data frame. Very cool, and more useful then I thought, but that is not what I wanted to talk about. I would like to give you some tips about working with someone you will probably work with in the future. [Read More]

Creating a package for your data set

Turning your dataset into a package is very useful for reproducable research. This tutorial is for you, even if you’ve never created a package in r. Why would you turn your dataset into a package? very easy to share easy to load (library(name) is easier then load("path/to/file") or data<-read.csv("path/to/file") etc.) documentation is part of the package and will never separate from data attributes of file remain nice and easy introduction to package building What do you need to do to create a dataset package: [Read More]

Portioning projects

Often we write programs to automate things. The programs range from simple to complex. But in essence, you always do the same thing: You are trying to solve a problem. A common pitfall, at least for me, is that you start out to big. What you need to do is start simple and small, and only if your simple thing works, increase the complexity. Separate parts of the program need to be separate functions. [Read More]