Matan Hakim

Exploring {ggplot2}’s Geoms and Stats – Stat’s What It’s All About

New blog post!

Ever wonder what geom_histogram is actually doing? How about geom_boxplot?

In celebration of the release of #ggplot2 4.0.0 (ggplot8?), I explore the relationships between the “geoms” and “stats” offered by the core {ggplot2} functions.

#rstats

ggplot2 4.0.0 A new major version of ggplot2 has been released on CRAN. Find out what is new here.

I am beyond excited to announce that ggplot2 4.0.0 has just landed on CRAN.

It's not every day we have a new major #ggplot2 release but it is a fitting 18 year birthday present for the package.

Get an overview of the release in this blog post and be on the lookout for more in-depth posts #rstats

Congrats, this should be a great organization!

a cookie monster is standing in front of a purple curtain and looking up ALT: a cookie monster is standing in front of a purple curtain and looking up

Is there a Mat(t)ans party?

fry from futurama is shown with a very serious look on his face ALT: fry from futurama is shown with a very serious look on his face

Not sure if cat's ear or piece of ginger

Beyond the 3-Point Revolution: A Deep Dive into NBA Shot Selection by Position and Distance How different positions have adapted to the changing landscape of NBA shooting

5/5
Final takeaway: The NBA is more specialized than ever. Centers are becoming true rim specialists, taking nearly 45% of their shots at the hoop. At the same time, the league is more homogeneous in its shot avoidance, with no one taking long mid-ranges anymore.

matanhakim.com/posts/2025-0...

4/5
The "3-point revolution" wasn't a single event. It happened in four distinct phases. For example, power forwards significantly increased their 3-point attempts around 2013, and centers followed suit a few years later. The data shows a staggered, positional adoption of the trend.

>>>

3/5
But it's not all about the 3-pointer. Interestingly, the 3-10 foot shot has made a comeback, especially for guards. This isn't random; it's a strategic counter-move to big men protecting the rim. Data reveals a nuanced offensive evolution beyond the arc.

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2/5
Data shows the long mid-range shot (16ft-3pt line) is practically extinct. It's plummeted from 24% of all shots to just 5%. Every position, from guards to centers, has abandoned this inefficient range. The data makes the conclusion clear: efficiency reigns supreme.

NBA Analytics with #Rstats Thread 1/5:
Ever wondered what the "3-point revolution" really looks like in the NBA? This thread dives deep into shot selection data from 1997-98 to today, using R to uncover some surprising positional and distance-based trends. #NBAData #SportsAnalytics

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Look awesome and I'm midway reading your book!
BTW there's a typo in the second element, "quality" rather than "qualify"

Holy crap where's the source code for that?!
Sign me up to contribute ☺️

I miss the "We're tickled pink" intro🥺

Looks good, thanks!

Hey @posit.co people, what's the best way to provide feedback about Shiny Assistant?

Talk about 3 and D

But indeed exciting altogether!

I guess this isn't the best example as it's hard to understand the color of the two least frequent groups

I haven't tried it myself yet, but I heard Typst is supposed to give you this kind of result.
See here:
quarto.org/docs/output-...

Today I finished teaching my ML for Psych in #rstats. The lesson was taught on zoom from my parents' attic, since our apartment was destroyed by an Iranian missile last week.

Class was interrupted by sirens, but resumed as if nothing happened after exiting bomb shelters - only in Israel!. 🇮🇱

Not sure if that's the use case you intend, but {pkgdown} takes 2 minutes to setup a website for your package

Data science junkies, get ready! 🚀 "The Test Set" #podcast trailer is here for your viewing pleasure.

Tune in July 1st and every Tuesday after for new episodes with hosts @mchow.com, @hadley.nz, and @wesmckinney.com as they welcome thought leaders in #DataScience.

Subscribe now: pos.it/thetestset

Are you looking for data consultants or subcontractors? My team at IICP is offering high-quality #RStats based analysis, viz & reporting—at nonprofit rates. Perfect for orgs or companies that want impact without breaking the bank.

Reposts & DMs are welcome!

See some of my work 👉 matanhakim.com

Cultural Data Science This book introduces basic concepts in data science, drawing from contextual examples in art history, visual computing, cloud computing, and microservices

Thrilled to share that my book Cultural Data Science – An Introduction to R is finally out! A journey through digital methods, visual culture & data analysis—made for everyone exploring the intersection of humanities and code.

#DigitalHumanities #RStats

link.springer.com/book/9783031...

Not sure if it is fitting for this specific use case, but {janitor} is an awesome toolbox for this kind of problems
sfirke.github.io/janitor/refe...

One of the best poems ever
apoemaday.tumblr.com/post/7396928...

While R is far from “dead” I do think we in the #rstats community need to consider this chart from @jscarto.

R has seen remarkable growth over the past decade, but has declined since 2022.

Why is this the case? Three notable things happened in 2022:

This looks great!
I'm having trouble installing the Rstudio version, where might be the best place to bring it up?

What advice do folks have for organising projects that will be deployed to production? How do you organise your directories? What do you do if you're deploying multiple "things" (e.g. an app and an api) from the same project?