Hi everyone, In this blog post, I will be short and I will introduce our shiny application on bike self-service stations. Your browser does not support the video tag. The code is in 2 parts, the ui.R file for the interface and the server.R file for the backend. You ... [Read more...]

How we taught a computer to understand Luxembourguish Today we reveal a project that Kevin and myself have been working on for the past 2 months, Liss. Liss is a sentiment analysis artificial intelligence; you can let Liss read single words or who... [Read more...]

This is part 3 of a 3 part blog post. This post uses the data that was scraped in part 1 and prepared in part 2. Now that we have the data in a nice format, let’s make a frequency plot! First let’s load the data and the packages:

library("tidyverse")
library("ggthemes") # To use different themes and colors
renert_tokenized = readRDS("renert_tokenized.rds")

Using the ... [Read more...]

This is part 2 of a 3 part blog post. This post uses the data that we scraped in part 1 and prepares it for further analysis, which is quite technical. If you’re only interested in the results of the analysis, skip to part 3! First, let’s load the data that we ... [Read more...]

This is part 1 of a 3 part blog post. This post presents the Luxembourgish language as well as the literary work I am going to analyze using the R programming language. Part 2 deals with preparing the data for analysis, and finally part 3 is the analysis. Hope you enjoy! Luxembourg and the ... [Read more...]

Hello everyone, In the last post we have decided to continue our study with the logistic regression. We have obtained the following ROC curve with an area under the curve (AUC) of 0.843. Now we imagine 2 scenarios. In the first one, we suppose we have a large budget and we want ... [Read more...]

Hello everyone, In the last post we have decided to continue our study with the logistic regression. We have obtained the following ROC curve with an area under the curve (AUC) of 0.843. Now we imagine 2 scenarios. In the first one, we suppose we have a large budget and we want ... [Read more...]

Hello everyone, Today we will make a churn analysis with a dataset provided by IBM. You can find the dataset here. What is a churn? We can shortly define customer churn (most commonly called “churn”) as customers that stop doing business with a company or a service. There are customer ... [Read more...]

Hello everyone, Today we will make a churn analysis with a dataset provided by IBM. You can find the dataset here. What is a churn? We can shortly define customer churn (most commonly called “churn”) as customers that stop doing business with a company or a service. There are customer ... [Read more...]

In this blog post, I show various ways to create maps using R. You’ll need to install a lot of packages and download two data sets; the unemployment rate in Luxembourg as well as a shapefile. To get the unemployment rate in Luxembourg, you can take a look at ... [Read more...]

Hello everyone, Why we always want to take the red pill when we can take the blue one? That’s the question! In this post I will explain how to launch a shiny application from a shortcut. Just like that: It’s fast and useful if you work with colleagues ... [Read more...]

You probably have encountered situations similar to this one:

result = vector("list", length(some_numbers))

for(i in seq_along(some_numbers)){
  result[[i]] = some_function(some_numbers[[i]])
}

print(result)

First I initialize result, an empty list of size equal to the length of some_numbers which will contains the results of applying some_function() to each element of some_numbers. Then, using a for loop, I apply the function. ... [Read more...]

After having watched Justice League in cinema, I was impressed by all of the special effects and how good they were. I started wondering myself: How much does a movie like that cost? And most importantly, how big is the box-office revenue for this kind of blockbuster? I found an ... [Read more...]

I think what I enjoy the most about functional programming is the peace of mind that comes with it. With functional programming, there’s a lot of stuff you don’t need to think about. You can write functions that are general enough so that they solve a variety of ... [Read more...]

One of my journalist friend was looking at the result of the local election in Luxembourg and he was dissatisfied because he was unable to compare the results of all the communes. In fact, he wanted to compare the number of women that were candidates in each commune. So I ... [Read more...]

Model interpretation is essential in the social sciences. If one wants to know the effect of variable x on the dependent variable y, marginal effects are an easy way to get the answer. STATA includes a margins command that has been ported to R by Thomas J. Leeper of the ... [Read more...]

Hello everyones, I just finished my MOOC on Foundations of strategic business analitycs. It was interresting and at the end of this course, I had to present a graph that was suppose to be relevent for a business organization. Different datasets were availables: speed dating, Co2 emissons, bike sharing, loans, ... [Read more...]

Update: I’ve included another way of saving a separate plot by group in this article, as pointed out by @monitus. Actually, this is the preferred solution; using dplyr::do() is deprecated, according to Hadley Wickham himself. I’ll be honest: the title is a bit misleading. I will not ... [Read more...]

Hello everyone, In this post we will focus on how to send a message from R to javascript. More precisely, we will focus on the basic keywords and knowledge to integrate a d3.js graph into shiny, just like here. If you have any issue to make shiny and javascript ... [Read more...]

First thing’s first: maybe you shouldn’t care about tidyeval. Maybe you don’t need it. If you exclusively work interactively, I don’t think that learning about tidyeval is important. I can only speak for me, and explain to you why I personally ... [Read more...]