R CODER | Jose Carlos Soage 📊

🎉🚀 Introducing R-PACKAGES.IO 🚀🎉 Discover & Explore R Packages, Functions, and Datasets like never before! 🌟 ✨ 20k+ Packages ✨ 400k+ Functions ✨ 40k+ Datasets The ultimate resource for R developers! 📊🔍 🔗 r-packages.io #RStats

@shadcn r-packages.io

Just realized I don’t have a list of apps using shadcn/ui. If you or your company’s using it in production, can you drop a link below? Thank you.

[Tip of the day] Write your R scripts like others will read them, because future you is someone else Comment generously, name clearly #rstats #CodeStyle

Just found this amazing {ggplot2} reference card – a lifesaver for customizing plots #rstats #dataviz

💡 Try {ggspatial} to easily add scale bars, north arrows, and basemap layers to your ggplot2 maps 🔗 r-packages.io/packages/ggspa…

💡 Struggling to get help with your R code online? Try {reprex} package to create a reproducible example that shows exactly what your code does Just write your code, run reprex(), and paste the result. Easy, clean, helpful. 👉 r-packages.io/packages/reprex

🌈 Try rainbow parentheses! They color each level of nesting so you can spot mismatches instantly. A simple trick, a huge difference for debugging 👇 #rstats #rstatsTips #DataScience #Productivity

🧵 How to clean data like a pro with dplyr and tidyr in R If you're still struggling with messy datasets or spending hours on manual cleanup… This thread is your shortcut to clean, tidy, analysis-ready data 👇 #rstats #DataCleaning #DataScience

📢 Si eres de España o LATAM y te interesa el mundo de la ciencia de datos… En mi LinkedIn personal (en español) comparto ideas, herramientas y reflexiones sobre IA, data science y emprendimiento 👤 ¿Conectamos? 👉 linkedin.com/in/jose-carlos…

@AdanBecerraPhD On r-coder.com/pie-chart-r/ I explain why should be used only with caution 👇

@AdanBecerraPhD You're absolutely right... pie charts often do more harm than good But they’re everywhere 😅

Found a great cheatsheet with different ways to visualize percentages and parts of a whole 📊 (Pie charts are just the beginning…) And if you work in R, I’ve gathered real code examples here: 🔗 r-charts.com/part-whole/ #rstats #DataViz #ggplot2 #DataScience

🚀 Want to write faster and more efficient R code? Check out Efficient R Programming — a practical guide packed with tips on writing clean, optimized, and production-ready R code. 🔗 csgillespie.github.io/efficientR/ #rstats #DataScience #Rprogramming #Productivity

🎯 Ever wondered what really sets apart a Data Analyst, Data Scientist, Data Engineer, and ML Engineer? They might sound similar, but each role has a different focus, skill set, and mission Let’s break it down 🧵👇 #DataScience #rstats #Statistics

👋 If you enjoy the R content I share here, you might also like what I post on my (new) personal account: data science, AI, and entrepreneurship Follow me at 👉 [@josecarlossoage ] Or on LinkedIn (in Spanish) 👉 linkedin.com/in/jose-carlos… #rstats #datascience

🔍 Drowning in forgotten TODOs in your R scripts? The {todor} package scans your code for #TODO, #FIXME, #NOTE, and more — so you can track your tasks like a pro ✅ 📌 Great for big projects 🧠 Never miss a fix 💻 Lightweight and easy to use 👉 install.packages("todor")

🦸‍♂️ Meet the newest superhero in town — Captain R! Fighting messy data, one line of code at a time 💪📊 Powered by tidyverse. Shielded by ggplot2 #rstats #DataScience #SuperCoder

[FREE R BOOK] 🚀 "Tidy Modeling with R" by Max Kuhn & Julia Silge is a must-read! 📘 Learn how to streamline your ML workflow using the tidymodels framework 🔗 tmwr.org #RStats #MachineLearning

🚀 This #ggplot2 tutorial by @CedScherer never gets old! 📊 One of the best resources to master beautiful plotting in R 🔗 cedricscherer.netlify.app/2019/08/05/a-g…

[FREE ONLINE BOOK] 📗 R Markdown: The Definitive Guide Learn how to create dynamic reports, presentations, and interactive documents with R Markdown! 🔗 bookdown.org/yihui/rmarkdow… #rstats #DataScience

I've been trying out different ways of creating dumbbell charts with {ggplot2}. For this one I used a 'wide' summary table for the source data (which feels more intuitive to me). The method owes a lot to this tutorial from @RCoderWeb: r-charts.com/distribution/d… #rstats #ggplot2