Shiny enables its users to quickly create a fixed UI with code. Although simple, this can prove to be quite limiting. Applying the principles of reactivity to the UI part of a ShinyApp is a natural progression from reactive coding as we know it already from Shiny’s server side. This blog entry reviews and discusses two of the most convenient tools for doing so.
Vom 09.-10. Oktober findet die Data University an der Goethe-Uni in Frankfurt statt, präsentiert von STATWORX & BARC.
What are driving factors behind the gas price? With freely accessible data we are goging to find out if the brand, the location and more have any impact on the price!
In time series context, one of most the commonly used measures is the MAPE. In this blog post, I evaluate critical arguments and weaknesses concerning the MAPE and demonstrate alternative measures.
Want to obtain a specific dataset from a website which does not have an API? In this post, I explain how to do this by scraping data using Python, how you determine whether it is allowed to scrape a specific page and more.
In this blog article, you will learn you how to set up a dashboard with the flexdashboard package, how to integrate interactive widgets and how to deploy the app on shinyapps.io.
Never heard of non-standard evaluation? Then our colleague Markus has the perfect answer for you: Bang Bang! In this blog post, Markus introduces meta-programming when using dplyr.
Monotoniebedingungen können helfen den Sachverhalt besser durch Modelle darstellen zu lassen. In diesem Beitrag wird erklärt wir man solche Monotoniebedingungen in R umsetzt.
It is June and nearly half of the year is over, marking the middle between Christmas 2018 and 2019. Last year in autumn, I’ve published a blog post about predicting Wham’s “Last Christmas” search volume using Google Trends data with different types of neural network architectures. Of course, now I want to know how good the predictions were, compared to …
In my last blog post, I have elaborated on the Bagging algorithm and showed its prediction performance via simulation. Here, I want to go into the details on how to simulate the bias and variance of a nonparametric regression fitting method using R. These kinds of questions arise here at STATWORX when developing, for example, new machine learning algorithms or …