In this month’s post, I set out to create a visual network of emotions. Emotion Dynamics tells us that different emotions are highly interconnected, such that one emotion morphs into another and so on. I’ll be using a large dataset from an original study published in PLOS ONE ...

DBnomics : the world’s economic database Explore all the economic data from different providers (national and international statistical institutes, central banks, etc.), for free, following the link db.nomics.world. You can also retrieve all the economic data through the rdbnomics package here. This blog post describes the different ways ...

So it is approaching AFL mens season, which means that soon everyones twitter feed, Facebook and emails will get clogged up with various tipsters. People saying they have won at 60% of the time over last season and therefor you should pay them money and follow their tips! But how can ...

Introduction If the practical tips for R Markdown post we talked briefly about how we can easily create professional reports directly from R scripts, without the need for converting them manually to Rmd and creating code chunks. In this one, we will provide useful tips on advanced options for styling, ...

Introduction If the practical tips for R Markdown post we talked briefly about how we can easily create professional reports directly from R scripts, without the need for converting them manually to Rmd and creating code chunks. In this one, we will provide useful tips on advanced options for styling, ...

We’ve released the newest version of NIMBLE on CRAN and on our website. NIMBLE is a system for building and sharing analysis methods for statistical models, especially for hierarchical models and computationally-intensive methods (such as MCMC and SMC). Version 0.7.1 is primarily a maintenance release with a couple important bug ...

I’m finishing a project from the RECSM institute where we developed a Shiny application to download data from the European Social Survey with Spanish translated labels. This was one hell of a project since I had to build some wrappers around the Google Translate API to generate translations for ...

As its been pointed out to me on that it would be handy if within fitzRoy that it should contain past players data from footywire. So here is roughly how to do that. Step 1 - get all the packages you need

library(rvest)

## Loading required package: xml2

library(tidyverse)

## ── Attaching packages ──────────────── tidyverse 1.2.1 ──

## ✔ ggplot2 3.1.0       ✔ purrr   0.3.0  
## ✔ tibble  2.0.1       ✔ dplyr   0.8.0.1
## ✔ tidyr   0.8.3       ✔ stringr 1.4.0  
## ✔ readr   1.3.1       ✔ forcats 0.4.0

## ── Conflicts ─────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter()         masks stats::filter()
## ✖ readr::guess_encoding() masks rvest::guess_encoding()
## ✖ dplyr::lag()            masks stats::lag()
## ✖ purrr::pluck()          masks rvest::pluck()

library(naniar)

naniar isn’...

Known user identity when building shiny apps can sometimes come really handy. While you can implement your own user login, for instance using cookies, you can also use some of the services which authenticate a user for you, such as Google. This way, yo...

We at STATWORX use mostly R or Python for our projects. But why not both? With the help of the reticulate package we can use Python within R. Here we show an example of how to train a Support Vector Machine. Der Beitrag R and Python: Using reticulate to get ...

Dirk Eddelbuettel just shared an important point on software and analyses: dependencies are hard to manage risks. If your software or research depends on many complex and changing packages, you have no way to establish your work is correct. This is because to establish the correctness of your work, you ...