Introducing Badgecreatr, a package to create and place badges in your readme.Rmd file on Github. Badgecreatr will create the following badges (aka shields): Installation Install the package with install.packages("badgecreatr") How do...

Introducing Badgecreatr, a package to create and place badges in your readme.Rmd file on Github. Badgecreatr will create the following badges (aka shields): Installation Install the package with install.packages("badgecreatr") How do you use badgecreatr? Badgecreatr has one main function: badgeplacer(). The most simple command is:

<span>badgecreatr</span><span>::</span><span>badgeplacer</span><span>(</span><span> </span><span>githubaccount</span><span> </span><span>=</span><span> </span><span>"yourgithubname"</span><span>,</span><span>githubrepo</span><span> </span><span>=</span><span> </span><span>"yourpackagename"</span><span>,</span><span> </span><span>branch</span><span> </span><span>=</span><span> </span><span>"master"</span><span>)</span><span>
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If ...

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. ...

This is the second part of working with ggplot. We will combine the packages dplyr and ggplot to improve our workflow. When you make a visualisation you often experiment with different versions of your plot. Our workflow will be dynamic, in stead of saving every version of the plot you ...

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/...

In this post we will start with a build-in dataset and some basic ggplot graphics. In the next post we will combine dplyr and ggplot to do awesome stuff with the Dutch University student counts from the previous lessons. We will work with the build-in dataset mtcars. There are many ...

Keeping track of versions You work on a project and would like to keep track of what you did. That is why keep old versions of your files. That way you can go back if you messed up beyond recognition. Usually that looks like this: Or you use dropbox or ...

Introduction To make analyses work we often need to change the way files look. Sometimes information is recorded in a way that was very efficient for input but not workable for your analyses. In other words, the data is messy and we need to make it tidy. Tidy data means 1: ...

Introduction In this lesson we will open a .sav file in Rstudio and manipulate the data.frame. We will select parts of the file and create some simple overviews. First time with R? No problem, see lesson 1 (https://rmhogervorst.github.io/cleancode/blog/2016/02/20/from-spss-to-r-part1.html#introduction “From spss to R, ...

Introduction This whole blog is devoted to R and clean coding in R. But what if you want to start with R? There are millions of websites devoted to learning R. just look at the number of hits on a certain search machine. Most of these hits start with the ...

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 ...