Carlos Gómez Grajales
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cgrajales.bsky.social
Carlos Gómez Grajales
@cgrajales.bsky.social
45 followers 170 following 26 posts
Statistics, data and prog metal. That's it.
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Reposted by Carlos Gómez Grajales
mackaszechno.bsky.social
Geocomputation. Faster and better than GIS even when Python available.
October 30, 2025 at 1:23 AM
Reposted by Carlos Gómez Grajales
nrennie.bsky.social
The making of this week's #TidyTuesday chart recorded with {camcorder} in #RStats 📹
October 23, 2025 at 3:04 PM
Reposted by Carlos Gómez Grajales
vincentab.bsky.social
The Pink Book of #MarginalEffects (aka Model to Meaning) ships next week and I've got a backlog of Zoolander memes.

Hope you're hungry for some spam in your timeline.

#RStats #PyData
September 22, 2025 at 4:52 PM
Reposted by Carlos Gómez Grajales
hrbrmstr.dev
The mlx_lm.server provides a rly nice OpenAI-compatible API server that serves up all the stored MLX models.
September 13, 2025 at 2:03 PM
Reposted by Carlos Gómez Grajales
grrrck.xyz
ggplot2 4.0.0 is out and the new `paper`, `ink`, `accent` theme variables look super cool! Just pick 2-3 colors 🎨 to make your plots look great! I'm excited to hook this up to brand.yml 😉
A ggplot2 plot showing a classic `mpg` scatter plot. The code uses `theme_gray()` with `paper = "cornstalk"` for a light yellow background, `ink = "navy"` for navy blue text and points, and `accent = "tomato"` which is applied to the smoothing line created with `geom_smooth()`
September 11, 2025 at 12:49 PM
Reposted by Carlos Gómez Grajales
dingdingpeng.the100.ci
Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...
Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities Abstract Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models). Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve. A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals). Illustrated are 1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals 2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and 3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.
August 25, 2025 at 11:49 AM
Reposted by Carlos Gómez Grajales
kennyvaden.bsky.social
Erosion (R code)

Inspired by the ancient phreatic flows of Mammoth Cave National Park

#codeart #genartclub #genart
August 20, 2025 at 3:58 AM
Reposted by Carlos Gómez Grajales
kylewalker.bsky.social
Two weeks ago, I gave a workshop on high-performance mapping apps with #rstats and Shiny.

Shiny is *awesome* for web mapping apps... but can be slow when deployed if you aren't careful.

Here are three strategies that have saved my projects:
July 21, 2025 at 5:39 PM
Reposted by Carlos Gómez Grajales
hrbrmstr.dev
Good #DuckDB vibes in today's Drop given all the horrible that happened today and this week in general.

— DuckPlot is a useful ObsPlot+DuckDB homunculus
— The DuckDB Viz MCP == no SQL req'd interactive dataviz
— DuckDB-QuickJS extension adds serious JS powers to DuckDB queries
Drop #672 (2025-06-27): If It Walks Like A…
We have another 🦆-billed Drop today, featuring: DuckPlot — an open-source JavaScript library for generating charts from DuckDB with automatic SQL generation; The mcp-visualization-duckdb package, w…
dailydrop.hrbrmstr.dev
June 27, 2025 at 4:51 PM
Reposted by Carlos Gómez Grajales
posit.co
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
June 18, 2025 at 4:58 PM
cgrajales.bsky.social
This is amazing on so many levels
statsepi.bsky.social Darren Dahly @statsepi.bsky.social · May 27
Once you see it...
A two panel image. On the left, a table of distributional characteristics (min, max, mean, sd) in columns for a set of variables in rows. One the right, a plot of that table, but also including the count of each, for which there were over 250000, whereas all the mins/maxs/means/sds were on the order of 1 or 10.
May 29, 2025 at 3:12 AM
Reposted by Carlos Gómez Grajales
chrisplummer.bsky.social
If you load this page it contacts 82 IP addresses executing 256 separate HTTP transactions to download 18MB of data writing 64 cookies to your device to tell you “no”
May 24, 2025 at 10:37 AM
Reposted by Carlos Gómez Grajales
dingdingpeng.the100.ci
Thanks to everybody who chimed in!

I arrived at the conclusion that (1) there's a lot of interesting stuff about interactions and (2) the figure I was looking for does not exist.

So, I made it myself! Here's a simple illustration of how to control for confounding in interactions:>
May 11, 2025 at 5:34 AM
Reposted by Carlos Gómez Grajales
t-kalinowski.bsky.social
Just made promptdown public. It's a plain-text interface for working with LLMs using literate programming.

See and edit the full prompt each turn.

No cramped input boxes, no hidden context, no append-only chat.

Still early alpha, feedback welcome!

github.com/t-kalinowski...
The package logo, a small cute elephant holding a quill and writing promptdown
May 8, 2025 at 3:36 PM
Reposted by Carlos Gómez Grajales
md.neuzerl.ing
You call it an ifelse statement, I call it a lightweight, agentic decision module operating within a deterministic inference framework
April 16, 2025 at 3:27 AM
cgrajales.bsky.social
👀 async
thomasp85.com Thomas Lin Pedersen @thomasp85.com · Apr 8
For the last couple of months I've been working on something and I'm excited to finally share an early preview:

Say hello to plumber2 🎉

plumber2 is a full rewrite of the plumber package for creating powerful webapis in #rstats. It takes everything we have learned from plumber and adds even more
What the Package Does (One Line, Title Case)
What the package does (one paragraph).
posit-dev.github.io
April 8, 2025 at 4:37 PM
Reposted by Carlos Gómez Grajales
brodriguesco.bsky.social
Thx to @ivelasq3.bsky.social for pointing me to this blog post of hers: ivelasq.rbind.io/blog/reticul...

I used it as an example to "port" the code to a rixpress pipeline which you can find here: github.com/b-rodrigues/...

end result is here: b-rodrigues.github.io/rixpress_dem...

#RStats #Python
Creating a dataset from an image using reticulate in R Markdown – %>% dreams
A cool paper used R and Python together — and so can you!
ivelasq.rbind.io
April 7, 2025 at 8:36 PM
Reposted by Carlos Gómez Grajales
hrbrmstr.dev
The base #RStats pipe (`|>`) is so stupid cool.
R code in the image: ```rstats xdf[,c("handle", "name", "description")] |> unique() |> within({ handle <- sub("^at://", "@", handle) md <- sprintf( fmt = "- (`%s`) %s%s%s", handle, name, ifelse(is.na(description), "", ": "), ifelse(is.na(description), "", description) ) }) |> sort_by(~md) |> getElement("md") |> writeLines() ```
April 5, 2025 at 7:15 PM
cgrajales.bsky.social
Loved this summary. This is incredibly relevant for data practitioners even beyond survey sampling.
April 3, 2025 at 11:16 PM
Reposted by Carlos Gómez Grajales
hrbrmstr.dev
Yesterday,
All Trump’s tariffs seemed so far away,
Now it looks as though they’re here to stay,
Oh, trade was better yesterday.

Suddenly,
We’re importing less from overseas,
There’s a tariff hanging over me,
The economy acts so suddenly.

1/3
April 3, 2025 at 5:29 PM
Reposted by Carlos Gómez Grajales
kylewalker.bsky.social
A new release of the {mapgl} #rstats package - which brings Mapbox and MapLibre maps to R users - is now on CRAN!

There are lots of long-awaited features in this new release.

Learn more on my blog: walker-data.com/posts/mapgl-...
March 20, 2025 at 2:15 PM
cgrajales.bsky.social
😍 Loved this in R but I needed it more in Python
posit.co Posit @posit.co · Mar 18
We are thrilled to announce Pointblank for data validation in Python!

With Pointblank, you can check your data against expectations and constraints, get a beautiful report table, and examine detailed step results and metrics.

Learn more in the blog post: posit.co/blog/introdu...

#Python
Pointblank data validation in Python
March 19, 2025 at 2:16 AM
cgrajales.bsky.social
Been consulting many big companies, for many years, and something like this has happened at some point in every single one of them.
tiddlydump.bsky.social tiddlydump.bsky.social @tiddlydump.bsky.social · Mar 12
When my org stood up our first DS team we did an audit of all the Tableau dashboards scattered to the four winds and turned off nearly 2/3 of them because they had viewcounts in the single digits per week.

Those were fun days
March 14, 2025 at 5:16 AM
Reposted by Carlos Gómez Grajales
baldurbjarnason.com
We’ve had three years of github copilot and two of chatgpt, both promising magical productivity gains for software dev, and the only change noticed by regular users is that everything keeps getting shittier, but now with more useless chatbots
March 10, 2025 at 10:09 AM
cgrajales.bsky.social
Fantastic resource for those of us (re) learning data viz and graphical story-telling
scientificdiscovery.dev Saloni @scientificdiscovery.dev · Mar 1
I made each of these graphs on ggplot2 and exported them to Adobe Illustrator to add further notes, titles, improve the legend, etc.

You can find scripts to recreate each of them here: github.com/owid/noteboo... The README file has a table to help quickly find each one.
Screenshot of readme file with table pointing to github folder for each chart.
March 6, 2025 at 5:15 AM