ππ Introducing R-PACKAGES.IO ππ
Discover & Explore R Packages, Functions, and Datasets like never before! π
β¨ 20k Packages
β¨ 400k Functions
β¨ 40k Datasets
The ultimate resource for R developers! ππ
π r-packages.io#RStats
[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
π‘ 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.
π r-packages.io/packages/repreβ¦
π Try rainbow parentheses!
They color each level of nesting so you can spot mismatches instantly.
A simple trick, a huge difference for debugging π
#rstats#rstatsTips#DataScience#Productivity
π§΅ 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 cleanupβ¦
This thread is your shortcut to clean, tidy, analysis-ready data π
#rstats#DataCleaning#DataScience
π’ Si eres de EspaΓ±a o LATAM y te interesa el mundo de la ciencia de datosβ¦
En mi LinkedIn personal (en espaΓ±ol) comparto ideas, herramientas y reflexiones sobre IA, data science y emprendimiento π€
ΒΏConectamos?
π linkedin.com/in/jose-carlos-β¦
π― 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
Letβs break it down π§΅π
#DataScience#rstats#Statistics
Found a great cheatsheet with different ways to visualize percentages and parts of a whole π
(Pie charts are just the beginningβ¦)
And if you work in R, Iβve gathered real code examples here:
π r-charts.com/part-whole/#rstats#DataViz#ggplot2#DataScience
π 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 π [@josecarlossoage ]
Or on LinkedIn (in Spanish) π linkedin.com/in/jose-carlos-β¦#rstats#datascience
π Drowning in forgotten TODOs in your R scripts?
The {todor} package scans your code for #TODO, #FIXME, #NOTE, and more β so you can track your tasks like a pro β
π Great for big projects
π§ Never miss a fix
π» Lightweight and easy to use
π install.packages("todor")
π¦ΈββοΈ Meet the newest superhero in town β Captain R!
Fighting messy data, one line of code at a time πͺπ
Powered by tidyverse. Shielded by ggplot2
#rstats#DataScience#SuperCoder
[FREE R BOOK]
π "Tidy Modeling with R" by Max Kuhn & Julia Silge is a must-read! π Learn how to streamline your ML workflow using the tidymodels framework
π tmwr.org/#RStats#MachineLearning
[FREE ONLINE BOOK] π
R Markdown: The Definitive Guide
Learn how to create dynamic reports, presentations, and interactive documents with R Markdown!
π bookdown.org/yihui/rmarkdownβ¦#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/duβ¦#rstats#ggplot2
ALT A dumbbell chart that shows reductions in average length of stay in an Acute Medical Unit (AMU) separately for 13 consultants. All consultants achieved reductions, but some reductions were bigger than others.
[FREE BOOK]
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
Written by Chester Ismay and Albert Y. Kim
π moderndive.com/
ππ Geocomputation with R is a free online book that covers everything from spatial data handling to advanced GIS analysis using R! ππ
Check it out here: r.geocompx.org/#RStats#GIS#Geocomputation