Building reproducible analytical pipelines with R Build reproducible analytical pipelines that will output consistent, high-quality analyses using the R programming language, Git, Github and Docker. Learn about functional and literate...continue reading.
My name is Bruno Rodrigues and hold a PhD in Economics from the University of Strasbourg. I’m currently employed as a statistician for the Ministry of Higher Education and Research...continue reading.
We’re thrilled to announce the release of dtplyr 1.3.0. dtplyr gives you the speed of data.table with the syntax of dplyr; you write dplyr (and tidyr) code and dtplyr translates...continue reading.
Hello and welcome to this new issue! How to have (my) content shared by R Weekly? This week’s release was curated by Eric Nantz, with help from the R Weekly...continue reading.
Just to remember where things are in my neovim installation in MacOS: The init file follows the structure presented in here: https://github.com/junegunn/vim-plug pointing to the location of the plugins as:continue reading.
There are multiple data science languages to choose from. The most popular being R and Python. Many people will tell you to learn both. Learn R AND Python. I think...continue reading.
Exploratory Factor Analysis (EFA) identifies a number of latent factors that explain correlations between observed variables. A key issue in the application of EFA is the selection of an adequate...continue reading.
Data visualization is important for communicating results. Selecting the right graphical representation of your data can enhance your data storytelling. In this article, I’ll show you how to implement drill-down...continue reading.
The standard procedure to create a Shiny app is straightforward. It involves a single app.R with a ui.R and server.R. But this simplicity also makes it difficult to build production-grade...continue reading.
Hello and welcome to this new issue! How to have (my) content shared by R Weekly? This week’s release was curated by Jonathan Carroll, with help from the RWeekly team...continue reading.
Artists who are women are underrepresented in art history textbooks, and we can use resampling to robustly understand more about this imbalance.continue reading.
The New Year Riddle is about optimisation: starting with a single machine, between delivering one unit per machine – hour and delivering one new machine per machine every six days,...continue reading.
Learn how to use Python’s f-strings for substitution and formatting, and then combine those features to solve a real-world pandas problem!continue reading.
In this final dplyr 1.1.0 post, we’ll take a look at two new verbs, pick() and reframe(), along with some changes to arrange() that improve both reproducibility and performance. If...continue reading.
Hello and welcome to this new issue! How to have (my) content shared by R Weekly? This week’s release was curated by Tony ElHabr, with help from the R Weekly...continue reading.
A recent social-media question by James Curran inquired about the best, or recommended ways, to extend R with Fortran code. Part of the question was whether the .Fortran() interface was...continue reading.
The first question that aspiring data scientists ask me is “what is the best data science language … which should I learn.” And almost always, this is framed as a...continue reading.
Today’s dplyr 1.1.0 post is focused on various updates to vector functions, like case_when() and between(). If you missed our previous posts, you can also see the other blog posts...continue reading.
R Shiny is a go-to technology when making apps and dashboards for companies using the R programming language. Shiny helps solve problems in complex business areas with large datasets, such...continue reading.
Today we are going to look at one of the major new features in dplyr 1.1.0, per-operation grouping with .by/by. Per-operation grouping is an experimental alternative to group_by() which is...continue reading.
Streamlit Tutorial: How to Deploy Streamlit Apps on RStudio Connect
February 25, 2022
