When it comes to our package, we wanted to add an automated way to get an overview - hence the name - of the data you are working with and present it in a neat and accessible way. Second, it is easy to share your code and new functions with others and thereby contribute to the engaged and vivid R community. First, it helps you to approach your problems in a functional way, e.g., by turning your everyday tasks into little functions and bundling them together. Writing a package has two main advantages. In the following sections, we will use a simplified version of one function ( overview_tab) from our overviewR package as a minimal working example. This tutorial seeks to close this gap: we will provide you with a step-by-step guide - seasoned with new and helpful packages that are also inspired by presentations at the recent virtual European R Users Meeting e-Rum 2020.
While there exist many great resources for learning how to write a package in R, we found it difficult to find one all-encompassing guide that is also easily accessible for beginners. That is exactly what we intended with our package overviewR. If you want to contribute to this community, writing a package can be one way. This is to a large part because of the active community that continuously creates and builds extensions for the R world. R is a great resource for data management, statistics, analysis, and visualization - and it becomes better every day.
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