I guess we all use it, the good old histogram. One of the first things we are taught in Introduction to Statistics and routinely applied whenever coming across a new continuous variable. However, it easily gets messed up by outliers. Putting most of the data into a single bin or ...

Two months ago padr was introduced, followed by an improved version that allowed for applying pad on group level. See the introduction blogs or the vignette("padr") for more package information. In this blog I give four more elaborate examples on how to go from raw data to insight with ...

When building a predictive model it is a good idea to do a univariate analysis, before throwing the whole bunch in a complex algorithm. This way we get a feel for the potential contribution of each predictor. When a lot of predictors are available one can often make a first ...

I am happy to introduce the padr package, which is now available on CRAN. If you frequently work with data containing a timestamp, especially automatically created data, you might find this package helpful. It solves two problems that you can be confronted with when preparing datetime data for analysis. First, ...

Maybe the following sounds familiar. You have a large data set with many, many columns of which the most are irrelevant to you. Typically, a dump from a database or the full set extracted from an API. Several times I found myself the better part of an afternoon going back ...

R has been an indispensable tool since I started working with it about five years ago. Of course in my day job as a data scientist I couldn’t live without it, but it also proved to be a great aid in private life. Recently we bought our first house ...