Carlos Gómez Grajales
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cgrajales.bsky.social
Carlos Gómez Grajales
@cgrajales.bsky.social
53 followers 180 following 30 posts
Statistics, data and prog metal. That's it.
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Reposted by Carlos Gómez Grajales
significancemag.bsky.social
The September 2026 issue is now published! academic.oup.com/jrssig/issue

Print copies will reach subscribers soon.

Non-subscribers, watch this space for links to the free-to-reads.
August 17, 2026 at 1:47 PM
Reposted by Carlos Gómez Grajales
kylewalker.bsky.social
I'm excited to share that I've received a grant from R Consortium to modernize R's tigris and tidycensus packages this summer.

Over the past decade, tigris and tidycensus have become fixtures in R's demographic and spatial data ecosystems.
July 17, 2026 at 1:32 PM
Reposted by Carlos Gómez Grajales
kwcollins.bsky.social
Very interesting survey of AAPOR members by Jon Cohen of TrueDot (formerly SurveyMonkey, formerly WaPo). Professional survey researchers are comfortable with many uses for Generative AI in survey research ... just not silicon samples
May 17, 2026 at 4:30 AM
Reposted by Carlos Gómez Grajales
juliusbogo.bsky.social
Hierarchical Bayesian models are easier than they sound. I used one to ask whether some Lithuanian news outlets are more negative than others. The naive answer was wrong; partial pooling fixed it. brms + ordinal regression on 4,832 headlines. jbogomolovas2.github.io/Julius-s-Blo...
“And I’m looking for the funnies”: sentiment in Lithuanian news headlines – Julius’s Blog
Data Science, Swimming Analytics, and R Programming
jbogomolovas2.github.io
May 3, 2026 at 3:25 PM
cgrajales.bsky.social
I need this on a t-shirt
evacide.bsky.social evacide @evacide.bsky.social · Feb 4
The people who think they are good at everything because they are good at coding are also bad at coding.
April 24, 2026 at 3:56 AM
Reposted by Carlos Gómez Grajales
dfalbel.bsky.social
We just released raghilda to PyPi. Raghilda is a framework for building RAG systems in #python. See the release blogpost: opensource.posit.co/blog/2026-04...
RAG with raghilda
An introduction to building retrieval-augmented generation systems with raghilda.
opensource.posit.co
April 15, 2026 at 4:57 PM
cgrajales.bsky.social
And not only among general public, very common to see this still needs to be discussed among data professionals 🤦
kwcollins.bsky.social Kevin Collins @kwcollins.bsky.social · Mar 29
A modest-sized but truly random sample of opinions is a better measure of opinions in the population than an enormous but self-selected sample of opinions from the same population
mnolangray.bsky.social M. Nolan Gray 🥑 @mnolangray.bsky.social · Mar 28
What's something that experts/practitioners in your field universally agree upon, but that remains a "hot take" among the general public?
March 30, 2026 at 4:36 AM
cgrajales.bsky.social
Forked
February 4, 2026 at 3:00 AM
Reposted by Carlos Gómez Grajales
jbengler.de
In case you ever wondered about the differences between magrittr pipe and base pipe 🤔

This table is taken from a great stackoverflow answer by @GeorgKindermann

stackoverflow.com/questions/67...

#rstats #dataviz #phd
February 2, 2026 at 5:39 PM
Reposted by Carlos Gómez Grajales
tslumley.bsky.social
It's also a case where the bootstrap doesn't work, and life is very much more pleasant if you're Bayesian and can just evaluate the ordering probability over a posterior sample
January 14, 2026 at 2:32 AM
Reposted by Carlos Gómez Grajales
johnholbein1.bsky.social
“These findings provide clear evidence that data collected on MTurk simply cannot be trusted.”
January 8, 2026 at 8:47 PM
Reposted by Carlos Gómez Grajales
kylewalker.bsky.social
2025 was a massive year for me as an R developer.

This past year I've branched out and focused on bringing interfaces to some of the most exciting geospatial technologies to the R community.

Here's a summary:
December 31, 2025 at 5:30 PM
Reposted by Carlos Gómez Grajales
nrennie.bsky.social
One of the things that has been on my to do list for a very long time, is building a gallery of all of the charts I've made across #TidyTuesday, #30DayChartChallenge, #30DayMapChallenge, and other miscellaneous projects 📊

And it's finally here!

Link: nrennie.rbind.io/viz-gallery/

#DataViz #RStats
Data Visualisation Gallery
Gallery of data visualisations created by Nicola Rennie.
nrennie.rbind.io
November 26, 2025 at 1:33 PM
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