Hi pharmaverse community, Continue reading: Novartis joins the Pharmaverse Council!
Here’s another puzzle, from Henry Dudeney’s Perplexities column in Strand Magazine, January 1924. Arrange the ten digits, 1 2 3 4 5 6 7 8 9 0, in such order that they shall form a number that may be divided by every number from 2 to 18 without ... Continue reading: Digital Difficulties
Have you ever wondered why your ggplot title is not perfectly aligned, detracting from the impact of your data visualization? As experts in data visualization and r programming, we understand the power of a well-... Continue reading: How to Center ggplot Title, Subtitle, and caption in ggplot2 with R
This is the second blog in a series about the {sparkline} R package for Continue reading: Sparklines in Reactable Tables
I am excited to announce that the pharmaverse council has approved additional organizational characteristics required for council membership. These criteria establish the level of DEI (Diversity, Equity & Inclusion) commitment we expect fr... Continue reading: Diversity Champion Updates
The BIST100 was rising before the Turkish Central Bank’s rate cuts; could that be an initial signal of a firm uptrend? The ML model tells us there is much more room to go up. Continue reading: Machine Learning Insights on BIST 100’s Future
This post is based on the textbook Evidence Synthesis for Decision Making in Healthcare (ESDMH) by Nicky J. Welton, Alexander J. Sutton, Nicola J. Cooper, Keith R. Abrams, and A.E. Ades. This textbook is an exemplary presentation of healthcare d... Continue reading: Evidence Synthesis for Decision Making in Healthcare
Call for Abstracts Deadline Extended Continue reading: Shiny in Production 2025: Abstracts Deadline Extension
What is data-driven art? At first I thought the answer to the question what is data art? would be relatively straightforward. I initially started with the definition that data art lies somewhere between data visualisation and generative art. Where data visualisation aims to accurately represent data to communicate insights, generative ... Continue reading: Creating data-driven art
R is packed with powerhouse tools—think dplyr for data wrangling, ggplot2 for stunning visuals, or tidyr for tidying up messes. But beyond the headliners, there’s a lineup of lesser-known functions that deserve a spot in your toolkit. These hidd... Continue reading: Underrated Gems in R: Must-Know Functions You’re Probably Missing Out On
Join our workshop on Effective Data Visualization in R in Scientific Contexts, which is a part of our workshops for Ukraine series! Here’s some more info: Title: Effective Data Visualization in R in Scientific Contexts Date: Thursday, April 10th, 18:00 – 20:00 CET (Rome, Berlin, Paris timezone) Speaker: Christian Gebhard is a ... Continue reading: Effective Data Visualization in R in Scientific Contexts workshop
We have great news: The call for applications to be part of the new cohort of our 2025 Program is now open! And for the first time it will be in Spanish! Continue reading: rOpenSci Champions Program 2025: In Spanish!
A blog post describing univariate and multivariate probabilistic forecasting of time series using Ridge2 and conformal prediction Continue reading: (News from) Probabilistic Forecasting of univariate and multivariate Time Series using Quasi-Randomized Neural Networks (Ridge2) and Conformal Prediction
The ShinyQDA R package is designed to assist researchers with the analysis of qualitative data. As the name suggests, the premise is that much of the interaction with the package will be done through a Shiny application. However, all the function... Continue reading: ShinyQDA: R Package and Shiny Application for the Analysis of Qualitative Data
In this post we are going to explore the relationship between sample size (n) and statistical significance for the chi-squared () test. Recall that from the normal distribution, we construct a confidence interval using: where z is the test stati... Continue reading: Sample size and statistical significance for chi-squared tests
I’m happy to announce 9 additions to the Big Book of R! Many thanks to Gary, Luis, Roger and Stephen for their contributions! The collection stands at almost 450 free, open-source (and some paid) books! Biological Data Science with R Introductory R book with a focus on tidy data analysis … Continue reading: 9 new books added to Big Book of R
R and Python implementations of word completion Continue reading: Word-Online: recreating Karpathy’s char-RNN (with supervised linear online learning of word embeddings) for text completion
Introduction Continue reading: Amending the Git commit message of a previous commit (that isn’t the most recent) in GitHub Desktop without performing an interactive rebase
This document describes some lower-level, technical details of the CRAN package ‘xdvir’ for rendering LaTeX fragments as labels and annotations on R plots. Paul Murrell ... Continue reading: 2025-01 LaTeX Typesetting in R
Join our workshop on Devops for Data Scientists (R & Python), which is a part of our workshops for Ukraine series! Here’s some more info: Title: Devops for Data Scientists (R & Python) Date: Thursday, April 3rd, 18:00 – 20:00 CET (Rome, Berlin, Paris timezone) Speaker: Rika Gorn is a Senior Platform Engineer at ... Continue reading: Devops for Data Scientists (R & Python) workshop
As the Common Crane (Grus grus) is Continue reading: Getting started with Crane
You can read the original post in its original format on Rtask website by ThinkR here: Customize your expedition: Create a unique documentation for your R Package Continue reading: Customize your expedition: Create a unique documentation for your R Package
Inspired by Roman A. Valiulin’s book NMR Multiplet Interpretation (discussed previously), I decided to write an R function to draw complex multiplets. The function will draw the multiplet, and optionally, can draw a splitting tree and some annota... Continue reading: A Function to Draw Complex Multiplets
Recreating the Hertzsprung-Russell Diagram in R Continue reading: Constructing the Hertzsprung-Russell Diagram
In my previous post, I outlined a Bayesian approach to proportional hazards modeling. This post serves as an addendum, providing code to incorporate a spline to model a time-varying hazard ratio non linearly. In a second addendum to come I will pres... Continue reading: A Bayesian proportional hazards model with a penalized spline
Announcement: teal 0.16.0 Release and Upcoming Community Meeting! We are excited to announce that teal 0.16.0 is now available on CRAN! Continue reading: teal 0.16.0 is released!
I was searching for one last real world example for my upcoming video talk March 13th on time series forecasting. Hope to see you there! Or reach out to Win Vector LLC for custom training! I had the seemingly harmless thought: “Let’s look at Stack Overflow trends“. In particular ... Continue reading: Best Before Dates by Bass
ahead, bayesianrvfl, bcn, learningmachine, esgtoolkit, new home Continue reading: CRAN-like repository for most recent releases ot Techtonique’s R packages
Working with clinical trial data is no small task. It needs to be precise, compliant, and efficient. Traditionally, this meant using proprietary tools and working within siloed systems, which often made the process more complicated and expensi... Continue reading: Working with Clinical Trial Data? There’s a Pharmaverse Package for That
In January, one hundred eighty-six new packages made it to CRAN. Here are my Top 40 picks in sixteen categories: Archaeology, Artificial Intelligence, Computational Methods, Ecology, Epidemiology, Finance, Genomics, Health Technology Assessment,... Continue reading: January 2025 Top 40 New CRAN Packages
The most valuable feedback often comes not from what users say, but from what they do! When was the last time you clicked a “Give Feedback” button in an app? Exactly. Yet product teams keep adding these explicit feedback mechanisms, hoping for insights that rarely materialize into actionable data. In ... Continue reading: Actions Speak Louder: Building Dashboard Features Users Actually Want
Hi pharmaverse community, Continue reading: Council Member updates
Open-source tools are growing in popularity within the pharmaceutical industry. Pharmaceutical companies such as Roche, Novo Nordisk, GSK, Johnson & Johnson, Novartis, Gilead, and Pfizer have all made significant contributions to open-source by providing insights into their integration of open-source technologies through shared open repositories. One of the examples are Boehringer ... Continue reading: Open-Source Adoption in Pharma: Opportunities and Challenges
Since the initial launch in 2021, our R-universe platform has steadily grown into a comprehensive infrastructure for publishing and discovering R material. Continue reading: Better documentation for R-universe!
Join our workshop on Frame-by-Frame Modeling and Validation of NFL geospatial data using gganimate in R, which is a part of our workshops for Ukraine series! Here’s some more info: Title: Frame-by-Frame Modeling and Validation of NFL geospatial data using gganimate in R Date: Thursday, March 27th, 18:00 – 20:00 CET (Rome, ... Continue reading: Frame-by-Frame Modeling and Validation of NFL geospatial data using gganimate in R workshop
Presenting 'Online Probabilistic Estimation of Carbon Beta and Carbon Shapley Values for Financial and Climate Risk' at Institut Louis Bachelier for the 18th FINANCIAL RISKS INTERNATIONAL FORUM Continue reading: Presenting ‘Online Probabilistic Estimation of Carbon Beta and Carbon Shapley Values for Financial and Climate Risk’ at Institut Louis Bachelier
Delivering the ShinyConf 24 keynote for the Shiny in Enterprise track, Eric Kostello, Executive Director of Data Science at Warner Brothers Discovery, discussed the instrumental role Shiny and its evolution has played in projects he has been involved in over the last decade. Big things are happening at ShinyConf 2025! Stay ahead ... Continue reading: ShinyConf24 – Keynote: Decade of Shiny in Action: Case Studies from Three Enterprises
Dear rOpenSci friends, it’s time for our monthly news roundup! You can read this post on our blog. rOpenSci HQ Open Science and Open Source only with Diversity, Equity, Inclusion... Continue reading: rOpenSci News Digest, February 2025
At Appsilon, we’ve been integrating Large Language Models into Shiny for Python applications for a while now. One thing became clear: the challenge isn’t in the initial integration. Shiny for Python’s ui.Chat component makes that straightforward. The real complexity lies in building applications that can evolve ... Continue reading: Building LLM-Powered Applications with Shiny for Python: Practical Insights
Data never stays in one place for long. Any business or team that works with data needs to be thinking about how data moves from one place to the next. This often happens multiple times, continuously, and in multiple different streams. The conce... Continue reading: You Don’t Need Airflow: Orchestrate Many Data Flows in R with Maestro
We are excited to invite you to the Appsilon Tiny Shiny Hackathon, a four-hour online challenge where developers can showcase their creativity and technical skills by building applications that combine Shiny and AI. ShinyConf 2025 is coming—are you ready? Join us for an exciting event filled with insights, innovation, and ... Continue reading: Sign Up for Appsilon’s Tiny Shiny Hackathon: Build, Compete, and Win!
The post Add Error Bars to Bar Plots in R Using ggplot2 appeared first on Data Science Tutorials Continue reading: Add Error Bars to Bar Plots in R Using ggplot2
Customizing the {riskassessment} App based on your organization’s needs makes validating R packages in regulated industries like pharma more efficient and compliant. Strict compliance rules and best practices mean organizations need a reliable way to assess and approve packages. The {riskassessment} App, built on {riskmetric}, provides a structured, user-friendly ... Continue reading: Shiny Gathering x Pharmaverse Recap: Simplifying R Package Quality with the {riskassessment} App
In the past, many organizations relied on static file reports to make decisions. Typically, several Excel and PowerPoint reports are generated each month. Management would gather, discuss results, decide, and move to email other systems or meet with their teams to pass these decisions forward. There are multiple problems with ... Continue reading: Scaling Decision Support Systems: When to Use React, Python, and R
Introduction Continue reading: Checking your R packages and practicals on a schedule using GitHub Actions
ggplot2 is a powerful and well-known data visualization package for R. But do you know what gg stands for? It actually refers to the Grammar of Graphics, a conceptual framework for understanding and constructing graphs. The core idea behind the Gramm... Continue reading: Demystifying geom_bar() – How ggplot2 Automatically Counts and Transforms Data
Join our workshop on Introduction to Empirical Macroeconomics with R, which is a part of our workshops for Ukraine series! Here’s some more info: Title: Introduction to Empirical Macroeconomics with R Date: Thursday, March 20th, 14:00 – 16:00 CET (Rome, Berlin, Paris timezone) Speaker: Xiaolei (Adam) Wang is an Economics PhD student ... Continue reading: Introduction to Empirical Macroeconomics with R workshop
This post reproduces Dr. Adam Bonica's analysis into the relationship between the ideological alignment of government agencies and the targeting of layoffs by the Department of Government Efficiency (DOGE). Continue reading: Political ideology and DOGE layoffs
The post Statistical Significance: Guide for Researchers and Analysts appeared first on Data Science Tutorials Continue reading: Statistical Significance: Guide for Researchers and Analysts
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