We’re hiring a Junior Systems Administrator! If you like solving problems, working with Linux, and keeping systems running smoothly, you’ll fit right in at Jumping Rivers. Find out more on our website. #Hiring #TechJobs #Linux #SystemsAdmin #JumpingRivers

We're hosting two meetups this month: 📍 20 Nov – Newcastle Myles Mitchell: Programming with LLMs in R & Python 🔗 www.meetup.com/newcastle-up... 📍 25 Nov – Leeds Dan & Dr Zeinab: LLM tools & explainability 🔗 www.meetup.com/leeds-data-s... Come join us 👋 #DataScience #AI

We’re at ISPOR Europe 2025, and you can find us at stand 1115. If you’re around, come say hi. We’re chatting about R, Python, Posit, and how teams build analysis platforms. Esther and Colin are here all through the event. We’ve got resources, hex stickers, and goodies! #ISPOREurope #RStats

We’ll be at ISPOR Europe 2025 in Glasgow from the 9th to the 12th! Looking forward to a few days of good conversations about data, open-source tools, and patient-centred innovation. If you’re attending, come say hi at the booth and look out for Esther and Colin from our team. #ISPOREurope

The inaugural @rainbowr.org #rstats conference has just been added jumpingrivers.github.io/meetingsR/ Thanks @statsrhian.bsky.social

In our latest blog post we compare the syntax of two Python libraries, Pandas and Polars for standard data-manipulation tasks. #python #polars #pandas

We wrapped Shiny in Production 2025 in Newcastle last week! It was two days of practical talks, async demos, UI sessions, and Shiny projects from healthcare, government, and research. Missed it? Our recap blog walks through everything we covered. #RStats #Shiny #DataScience #Python #OpenSource

Data dashboards are our passion at Jumping Rivers. Earlier this year, we created a gallery to demonstrate our application-development capabilities. #Rstats #Data #Dashboards

We are happy to share that we'll be at ISPOR Europe next week. If you are attending come by, and say hello! #Rstats #Conference #Networking

Creating well-structured Python packages is essential for reproducible, scalable code. In our blog series, we demonstrate how to use Poetry to create a Python package. #Python #Poetry #SoftwareDevelopment #PackageManagement

Diffify is a platform that compares different versions of R packages (from CRAN) and Python packages (from PyPI). It helps you quickly see what's changed between the package version you're using and newer releases, including updates from NEWS files, dependencies, namespaces, functions. #R #Python

If your Posit Team products setup isn't working for you, or you've encountered bugs, our Posit Health Check is for you. Our team of Posit experts can review your configuration for you and ensure it's set up correctly, so you can get the most out of your Posit products. #PositHealthCheck

Just added Bioc 2026 to the list of next year's #rstats conferences jumpingrivers.github.io/meetingsR/

In our latest post in our Python package development blog series, we discuss how to create a package in python, add documentation, testing and publish to PyPI. #datascience #package #development #python

Python 3.14 was released on 7th October. In our latest blog post we summarise the most interesting changes to the Python ecosystem in 2025 that affect data science. #Python #DataScience

Just added @posit.co Conf 2026 to the list of conferences. Let us know if we've missed any! #rstats jumpingrivers.github.io/meetingsR/ev...

First #rstats conference of 2026 added to jumpingrivers.github.io/meetingsR/ev... @user-conf.bsky.social 2026 in Poland

Our latest blog post is about Kubernetes! Our very own Shane Halloran shares real-world lessons from deploying Posit Workbench on Azure Kubernetes Service (AKS), including practical debugging tips, and the importance of looking beyond the cluster when issues arise. #RStats #Kubernetes #Azure

Do you have a package you want us to assess at #positconf? Let us know, and we’ll present the results at the lunch and learn. jumpingrivers.typeform.com/to/FfWU3pV1 #rstats

In our latest blog post we introduce the ARIMA framework for time series forecasting and demonstrate the process using a real world example with Python. www.jumpingrivers.com/blog/time-se... #DataScience #python #timeseries

For quite some time, AI had kept it's grubby little hands out of the music production world. To learn more about the impact of AI in music production read out latest blog post! #AI #MusicProduction #DataScience

The Shiny in Production Conference is fast approaching — and we couldn’t make it happen without the incredible support of our sponsors! A big thank you to: - Posit - ThinkR - Datacove - Newcastle University Solve - CRC Press - R Consortium #RStats #DataScience #ShinyInProduction #Sponsors

In our latest blog post, our Data Scientist Osheen MacOscar shares a great overview of how to use {ggplot2} and {gganimate}, when dealing with spatial data. #rstats #datavis #spatialdata #maps

Web content accessibility is an important topic to consider when building web based applications. {shiny} is an excellent tool that allows data practitioners a relatively simple, quick approach to providing an intuitive user interface to their R code via a web application. #rstats #shiny

Do you use R? Would you like to play a part in sustaining it? Find out about the R Dev Day that is returning as a satellite event to Shiny in Production 2025. #rstats #rshiny #ShinyInProduction #conferences

Jupyter notebooks are a popular tool for data scientists using Python. They allow us to mix together plain text (formatted as Markdown) with Python code. In this post, we will show you how to produce reproducible PDF and HTML reports from a Jupyter notebook using Quarto. #rstats #python #quarto

We had an fantastic evening with our community, thank you to everyone who joined us. Special thanks to our speakers Colin Gillespie and Paul Goodman for delivering main talks, and to Aida Gjoka for leading the pre-event workshop. See you all at our next meetup in November! #DataScience #rstats

Importing data is a key step in the data science workflow. In our latest Python blog post, we compare this process for two key libraries - Polars and Pandas - emphasising how to convert to the correct data-type and why you should validate the structure and content of the imported data. #rstats

As data scientists we often need to communicate conclusions drawn from data. In this blog post we will look at how Quarto allows us to weave together text and Python code to generate automated reports. #rstats #python #quarto #reporting

We had a wonderful time at Leeds Data Science Meetup last night! Thanks to everyone who joined and special thanks to our speakers Hugh Evans and William Martin for their insightful talks. Looking forward to seeing you all at our next meetup! #LeedsDataScience #DataScience #TechMeetup#Leeds#Leeds

New blog post: "Litmus: Maintainer Criteria" How often do bugs get fixed? Does the package use source control? Is it a solo or group effort? These critical questions help assess the long-term viability and risk profile of R packages in your workflow. #RStats #DataScience #PackageValidation

Just added the November #rstats+#ai event to jumpingrivers.github.io/meetingsR/ev... Are there any other events missing?

Code quality is what typically comes to mind when talking about "good packages". Does that package pass standard checks? What is the Unit test coverage? How many dependencies does the package have? This post discusses how we use code quality when determining the package litmus score. #rstats

Python package managers are essential tools that help developers install, manage, and update external libraries or packages used in Python projects. These packages can contain reusable code, modules, and functions developed by other programmers. #rstats #python #packagemanager

Are you ready to expand your knowledge in R, Python, Shiny, and Posit while becoming a more valuable asset to your team? Jumping Rivers is here to help you do just that with our free monthly webinar series designed for data professionals at all levels. #rstats #webinar #upskill #datascience

As part of our #rstats validation, we scan the dependencies for all CRAN packages. Surprisingly, the median number is only 3 (the maximum is 49).

Not all R packages are clearly “good” or “risky”, most fall somewhere in between. This post introduces our scoring framework around package documentation. We investigate the different measures, then look at a few well known packages. #rstats #packagevalidation #softwaredevelopment

Talking at Manchester #rstats meetup tonight. There will be maps, geology, plesiosaurs, software design and pizza / beer. meetu.ps/e/Nx6kN/rmsg... (First new talk in a year, still under edit) Also Mark Webster is talking about {autodb} cran.r-project.org/web/packages...

In regulated industries, Shiny apps must be reliable, reproducible, and well-documented. Learn how to avoid common pitfalls and set up a lightweight, effective validation approach that scales with your needs. #rstats #ShinyAppValidation #testing

We are happy to share that alongside nine full-length sessions, this year’s conference (8–9 October) also features a lineup of fast-paced 5‑minute lightning talks. #ShinyInProduction #RStats #RShiny #ShinyApps #DataScience

The popularity of an R package can be measured using package downloads and reverse dependencies. While these measures clearly have issues, they do provide a good indication of the package health. Our latest blog post looks at these measures in more detail. #rstats #validation #litmus

This year’s Shiny in Production Conference workshops cover the key aspects of building effective, production-ready Shiny apps: Testing for {shiny}, Asynchronous Shiny, Maps in Shiny, Figma & UI Design for Shiny. #ShinyInProduction #RStats #RShiny #ShinyApps

Validating Shiny Apps in Regulated Environments by our Data Scientist Pedro Silva at R/Medicine is now out! In this talk, Pedro explores how to make Shiny apps trustworthy and compliant in regulated settings. #RStats #Shiny #RMedicine2025 #Validation #ClinicalResearch #PharmaTech #Litmusve

At Jumping Rivers, we've developed a scoring framework to help users assess R package quality. Our latest blog post, "R Package Quality: Validation and Beyond!", walks through this new framework and shares guiding principles that ensure the scores are fair, flexible, and context-aware. #rstats #R

We're happy to share the main talks for the Shiny in Production Conference 2025! This year's lineup includes some great talks on using Shiny in real-world projects, from building apps to scaling them in production. Looking forward to seeing everyone there! #ShinyInProduction #RStats #DataScience

Early bird registration for the Shiny in Production Conference closes at the end of the month, grab your ticket before then! We'll be announcing the selected speakers in the coming days. #ShinyInProduction #RStats #DataScience#Shiny#Shiny

We're happy to share that our Data Scientist, Pedro Silva, will be speaking at R/Medicine this Thursday. He’ll be presenting on “Validating Shiny Apps in Regulated Environments”, an important topic for anyone working with R in clinical or regulated settings. #RMedicine2025 #RStats #ClinicalResearch

Exploring the use of d3.js for a #rstats project. Found this post from @jumpingrivers.com's to be a good entry point: www.jumpingrivers.com/blog/r-d3-in... Digging further into the 📦 {r2d3}: rstudio.github.io/r2d3/index.h..., which is useful for interfacing D3 with R. #dataBS

Our latest blog post is about dealing with images on web pages - a task that used to be straightforward but has been made more complex in recent years by high-density screens and new file-formats with varying levels of browser support.

In this week’s blog post, our Data Scientist Theo Roe shares a great introduction to the {officer} package in R. The {officer} package lets R users work directly with Word and PowerPoint documents. Learn more: www.jumpingrivers.com/blog/custom-... #RStats #DataScience #Reporting #Automation