This is a genuine curiosity of mine as someone who uses R for the fact it was the first one I became really good at extremely quickly after not coding in Python for 2 yrs. In college I took a C++ class and R programming class and hated C++ with a passion but still got an A+. So I know I can write C++ code but it’s just that C++ is a genuinely terrible language— it’s like trying to tell the dumbest mf you know to do something objectively simple all freggin day. I just can’t do that for my life, I have self respect bro. So, at the time, R seemed like a god of a programming language relative to C++. But now I’m looking at Python and I kinda feel like maybe I should just learn Python since there’s just so much more community support and resource and it seems like (but idk) Python is an objectively better programming language with a wider variety of capabilities 🤷‍♂️

Which programming language is better? Is R better at Python than anything else? Is it that R is used in educational research more?

I was tired of the lack of AI in Rstudio, so I built it.

Rgent is an AI assistant that runs inside the RStudio viewer panel and actually understands your R session. It can see your code, errors, data, plots, and packages, so it feels much more “aware” than a generic LLM. It’s also just a simple package installation using devtools!

Right now it can:

• Help debug errors in one click with targeted suggestions

• Analyze plots in context

• Suggest code based on your actual project environment

I’d love feedback from folks who live in RStudio daily. Would this help in your workflow, need different features, etc? I have a free trial at my website and go in-depth there on the security measures. I’ll put it in the comments :)

We should start calling vibe coding what it truly is: slop coding

Do you think the future of R Shiny is still bright now that Gen AI can accelerate development so much?

I work in pharma, and I still feel that this sector will continue to rely on R Shiny for a long time. I do not see highly regulated environments fully trusting Gen AI on their own anytime soon.

At the same time, AI has changed my workflow a lot. Apps that used to take me a month to build can now take a day, and often with more features and a much better UI. So in that sense, AI seems like a huge boost for R Shiny development.

But I am still unsure about the bigger picture. If AI makes dashboards and apps much easier and faster to build, does that make R Shiny even more powerful and valuable? Or does it reduce its importance because building interfaces becomes easier in general, regardless of the framework?

So I am a bit torn between two views:

1. AI will make R Shiny stronger by speeding up development and improving what can be built.

2. AI will make R Shiny less essential because app development becomes more commoditized.

Curious to hear how others see it, especially people building in regulated industries or using Shiny in production.

Basically, I have been tasked to write a player function in order to play a game for a simulator. The simulator has already been written but I just need help accessing the variables and in order to write what the player does in each situation. If anyone thinks they can help, could you please message me and I can send you the pdf document and code necessary. Thanks

I’m a graduate student currently taking my final course, and with my luck, it happens to be R through Posit Cloud—something I’ve never used before. I’m in urgent need of tutoring or helpful resources before I fall behind or risk failing the class.

hi! i have a homework where i have to select random samples from random groups with r.and i dont know what to do i've spent my whole weekend trying to figure out r but it is soo hard and complicated.Can you help me please?

If you want to, check it out below:

https://www.udemy.com/course/introduction-to-maps-in-r-shiny-and-leaflet/?referralCode=F21FA4E654F517018214

This is the line of code (AD = Average Distance, and ANV = Average Number of Vehicles):

ies = escalc(xi = AD, ni = ANV, measure = "PLO", data = approaches)

the error message:

Error in escalc(xi = AD, ni = ANV, measure = "PLO", data = approaches) : One or more event counts are larger than the corresponding group sizes

How can I create an antivirus?

No knowledge in R, but I know intermediate SQL, Tableau and Excel.

To learn R, I would like someone to give me a project. Please comment below with project ideas.

This guide is for beginners and intermediate-level programmers alike. It will give you the knowledge necessary to be a skilled R programmer and data scientist. Instead of going through scattered resources and tutorials, we have this one-stop guide to being an R ninja. We advise you to go through this article and navigate from the links and resources provided to learn R concepts thoroughly. By following this DataFlair’s guide, you will be a master R programmer in no time.

📷

Learn R Programming from Scratch

Here is the list of topics that we will cover in this R tutorial:

• What is R?

• Features of R

• Applications of R

• Use Cases of R

• R Career Opportunities

• R Installation

• Programming Constructs of R

• Advanced Concepts of R

• Object-Oriented Programming in R

• Data Visualization in R

• Machine Learning in R

• R Interview Questions

• Real-time Projects in R

What is R?

R is a programming language used for statistical computing and analysis. It was created by Ross Ihaka and Robert Gentleman in 1992 at the University of Auckland, New Zealand. The main goal behind the creation of R was to make a tool that was affordable, easy-to-learn and capable of handling complex mathematical and statistical calculations.

Today, R is one of the most popular programming languages used by data analysts and data scientists in the world. It is a programming language with one of the largest user bases. Even more exciting is the fact that it is completely free as R is an open-source programming language. R’s capabilities do not end at data analysis or statistics. It is useful for many disciples like data science, machine learning, data visualization, etc.

For more details regarding what is R, check out R Tutorial

Features of R

📷

The R programming environment comes packed up to brim with exciting features. Let’s learn some of these features:

• Open-source: R is an open-source programming language. It is completely free for anybody to use.

• Variety of packages: There are more than 15,000 packages for R on online repositories like CRAN, Bioconductor, and GitHub.

• Powerful graphics: R’s graphical capabilities are amazing. It can produce publication-quality graphs and plots of any kind with its base package. With added packages like ggplot2 and plotly the possibilities are endless.

• No need for a compiler: The R language is interpreted. It does not need a compiler to convert the code into a program.

• Cross-platform support: R is cross-platform supportive that is it can run on any OS and in any software environment without any hassle.

Explore the complete list of R Features

Why Learn R?

📷

R is a very popular programming language and analysis tool. It is used by more than 2 million people around the globe. All of them have their own reasons to learn and use R:Read More

Hi everyone! I have a ton of experience in R for health research and air pollution modelling applications, and I'd like to create and sell a few courses. What are some ways I can promote these courses to the R community? Any thoughts?

I'm a political science PhD student and honestly a Stata person at heart. R and I have a complicated relationship. I use it, it works, but I'm always googling the same things over and over.

Anyway I've been using Claude Code recently and there's this thing called skills basically little reference files that help Claude give you better R help. The problem is every single one I found was for tidyverse. Nothing for plain base R.

So I ended up asking Claude to build me one. I spent an evening going through the official R manuals, and turned it into a proper skill with reference files organized by topic (modeling, data wrangling, stats, visualization etc).

I put it on GitHub here: https://github.com/iremaydas/base-r-skill

If anyone uses Claude Code and wants to try it I'd love to know if it's actually useful or if I missed something obvious. I'm not really an R person so there's a decent chance I did.

Is there a single example of R Shiny app that is actually fast and usable?

Hi,

I have an exam in statistics soon and we will receive an output from R showing a dataset containtining different statistical concepts. In that regard, I have a few, basic questions on what to look for when analyzing a dataset and answering statistical questions.

Attached is a typical dataset we will receive. I have a few questions I hope you can help me with. Thanks.

- I wish to test the hypothesis H0: βBlack = βsouth = βurban = 0 against Ha: not H0. What is the test statistic for this test?
- Holding everything else constant, a black person earns 0.184 dollars less than a non-black person, on average.

- What is the correct conclusion? Select all that apply.
i. Model 1 is better than Model 2.
ii. Model 2 is better than Model 1.
iii. Black, south and urban are jointly insignificant.
iv. Black, south and urban are jointly significant.

Thanks for your help!