#PyData
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dslc.io
It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io!
#RStats #PyData #JuliaLang #RustLang #DataViz #DataScience #DataAnalytics #data #tidyverse #DataBS
November 3, 2026 at 7:42 PM
fsse8info.bsky.social
pydata london meetup @ liverpool st #webdev
room
November 4, 2026 at 6:59 PM
voip8info.bsky.social
pydata london meetup @ liverpool st #webdev
room food
November 4, 2026 at 6:58 PM
voip8info.bsky.social
pydata london meetup @pydatalondon.bsky.social @janestreet.bsky.social #webdev
world map agenda benchmark
November 4, 2026 at 7:21 PM
madrid.pydata.org
#PyDataMadrid comes back in November, this time at the new @jetbrains.com offices in Madrid!

We'll have talks by Cristina Marquez about AI applied to build virtualized 5G networks (en español) and @cheuk.dev on the debate of AI consciousness (in English)

Save your spot, space is limited!

#PyData
🧬 ¿Es la IA consciente? e IA aplicada a redes 5G virtualizadas | Guild
Nov 12th 7:00PM: \[SPA] PyData Madrid vuelve el 12 de noviembre para hablar de Python, datos e inteligencia artificial, ¡Y lo que surja! Este mes nos reuniremos en la sede de Jetbrains (Paseo de la ...
guild.host
November 5, 2026 at 11:47 AM
dslc.io
It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io!
#RStats #PyData #JuliaLang #RustLang #DataViz #DataScience #DataAnalytics #data #tidyverse #DataBS
jonthegeek.com Jon Harmon (he/him/his) @jonthegeek.com · 11d
@dslc.io welcomes you to week 43 of #TidyTuesday! We're exploring IKEA Sofas and Their Swedish Places!

📂 https://tidytues.day/2026/2026-10-27
📰 https://karaman.is/ikea-place-names

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds
Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash. TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag. Map of Sweden with a dot for each place that shares its name with an IKEA sofa or armchair in the Swedish range. Filled dots are sofas, hollow dots armchairs, and ringed dots names used for both. The dots are densest in the south, especially in Skåne, Småland and around Stockholm, and thin out towards the north, where only a handful sit in the interior of Norrland. A red cross marks Älmhult in Småland, where IKEA started. One place, Herråkra in Småland, is highlighted with its name in a blue label.
October 27, 2026 at 6:09 PM
mitchhenderson.bsky.social
I turned the tracking data into a small number of interpretable features based on football concepts and built a simple Bayesian model that predicts play success as well as a neural net.

Data available. Code in #rstats and #pydata. Model written in Stan and PyMC.

mitchhenderson.dev/posts/2026-1...
Sometimes interpretability doesn’t cost predictive power – Mitch Henderson
This was one of those times
mitchhenderson.dev
October 29, 2026 at 7:46 PM
jonthegeek.com
@dslc.io welcomes you to week 44 of #TidyTuesday! We're exploring Grambank!

📂 https://tidytues.day/2026/2026-11-03
📰 https://www.science.org/doi/10.1126/sciadv.adg6175

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds
Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash. TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag. This map displays the global distribution of language samples coded in the Grambank dataset on a world map centered on the Pacific Ocean. Light yellow landmasses contrast against light blue oceans, with thousands of white dots representing sampled languages scattered across the globe. Sampling density varies significantly by region: the highest concentration of overlapping dots covers Papunesia (New Guinea, Island Melanesia, Australia), Southeast Asia, Sub-Saharan Africa (particularly West, Central, and East Africa), Mesoamerica, and the Andean/Amazonian regions of South America. Moderate density extends across North America (notably the West Coast), Western Europe, the Caucasus, and South Asia along the Himalayas. Lower density appears across northern Eurasia (Siberia), interior Australia, and northern North America, reflecting underlying regional language distribution and data coverage. A 4-panel scatter plot grid (A–D) compares variance explained by phylogeny (x-axis, 0–100%) versus geography (y-axis, 0–100%) across four linguistic domains, each featuring points with shaded confidence ellipses and a dashed diagonal reference line. Panel A (clause, red circles) clusters at 50–90% phylogenetic variance and 0–20% geographic variance, plus one outlier near 5% phylogeny and 20% geography. Panel B (nominal domain, orange squares) clusters at 75–100% phylogenetic variance and mostly under 25% geographic variance. Panel C (pronoun, purple diamonds) concentrates tightly in the bottom-right corner at 75–100% phylogenetic variance and near 0% geographic variance. Panel D (verbal domain, cyan triangles) clusters heavily at 75–100% phylogenetic variance with minimal geographic variance, except for an outlier near 35% phylogeny and 25% geography. Across all domains, variation is overwhelmingly driven by language family history over spatial proximity.
November 2, 2026 at 8:46 PM
carlkadie.bsky.social
Vibe validation offers a way to trust vibe-coded algorithms: AI writes a spec and proof; Lean checks it; humans review the model and spec.

My PyData Seattle / @microsoft.com Reactor talk demonstrates this for Python and Rust algorithms.
www.youtube.com/watch?v=P9xC...
Beyond Vibe Coding: Formal Verification for AI-Generated Software
YouTube video by Microsoft Reactor
www.youtube.com
October 26, 2026 at 3:25 PM
jonthegeek.com
@dslc.io welcomes you to week 43 of #TidyTuesday! We're exploring IKEA Sofas and Their Swedish Places!

📂 https://tidytues.day/2026/2026-10-27
📰 https://karaman.is/ikea-place-names

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds
Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash. TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag. Map of Sweden with a dot for each place that shares its name with an IKEA sofa or armchair in the Swedish range. Filled dots are sofas, hollow dots armchairs, and ringed dots names used for both. The dots are densest in the south, especially in Skåne, Småland and around Stockholm, and thin out towards the north, where only a handful sit in the interior of Norrland. A red cross marks Älmhult in Småland, where IKEA started. One place, Herråkra in Småland, is highlighted with its name in a blue label.
October 26, 2026 at 5:23 PM
quansight.com
SQL shows up everywhere: job interviews, every company, even grocery shopping, according to Marco Gorelli. Most comparisons with Polars stop at syntax and speed. Marco takes it further.
Watch the full talk: buff.ly/7ivcj9C
#SQL #Polars #DataScience #PyData #OpenSource
October 23, 2026 at 4:22 PM
bschneidr.bsky.social
New small blog post on why sometimes you should just write SQL instead of using #rstats or #pydata packages that write SQL for you.

www.practicalsignificance.com/posts/someti...
Sometimes You Should Just Write SQL – Practical Significance
There are lots of amazing tools like dplyr or Ibis that let you avoid writing SQL. But sometimes you just have to write SQL.
www.practicalsignificance.com
October 22, 2026 at 3:32 AM
nocomplexity.bsky.social
Is That Python Script Safe? How to Check Before You Run.

nocomplexity.substack.com/p/how-to-saf...

#python #pydata #coding
How to Safely Use Python Programs from Untrusted Sources
Is That Python Script Safe? How to Check Before You Run
nocomplexity.substack.com
October 23, 2026 at 5:54 AM
dslc.io
It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io!
#RStats #PyData #JuliaLang #RustLang #DataViz #DataScience #DataAnalytics #data #tidyverse #DataBS
jonthegeek.com Jon Harmon (he/him/his) @jonthegeek.com · 18d
@dslc.io welcomes you to week 42 of #TidyTuesday! We're exploring Which College Majors Are Safest From AI (and Do They Pay)?!

📁 https://tidytues.day/2026/2026-10-20
📰 https://arxiv.org/abs/2303.01157

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds
Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash. TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag. Scatter plot of 285 bachelors majors comparing the AI exposure of the occupations each major leads to (x-axis, left is least exposed) against median starting salary one year after graduation (y-axis). Points are green when a major is in the safer, higher-paid half and purple when more AI-exposed. Bubble size shows the number of graduates measured. The points are spread out with no real correlation between AI exposure and starting salary. Registered nursing, nuclear engineering technology, and marine transportation are safe from AI and well paid, while English and philosophy are among the most exposed and lowest paid.
October 20, 2026 at 5:30 PM
jonthegeek.com
@dslc.io welcomes you to week 42 of #TidyTuesday! We're exploring Which College Majors Are Safest From AI (and Do They Pay)?!

📁 https://tidytues.day/2026/2026-10-20
📰 https://arxiv.org/abs/2303.01157

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds
Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash. TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag. Scatter plot of 285 bachelors majors comparing the AI exposure of the occupations each major leads to (x-axis, left is least exposed) against median starting salary one year after graduation (y-axis). Points are green when a major is in the safer, higher-paid half and purple when more AI-exposed. Bubble size shows the number of graduates measured. The points are spread out with no real correlation between AI exposure and starting salary. Registered nursing, nuclear engineering technology, and marine transportation are safe from AI and well paid, while English and philosophy are among the most exposed and lowest paid.
October 19, 2026 at 5:29 PM
pydatastl.bsky.social
Missed our October 13 PyData St. Louis event?
The recording is now available!
Dr. Cassandra Collier joined us to discuss how AI is changing the role of data analysts and the future of analytics.
🎥 www.youtube.com/watch?v=yvlD...
#PyData #DataAnalytics #AI
The Data Analyst Isn’t Disappearing, but the Job is Changing - Cassandra Collier
Generative AI is increasingly capable of performing tasks that have traditionally been central to data analytics, from writing code and cleaning data to creating visualizations and generating…
www.youtube.com
October 16, 2026 at 1:01 PM
cpsievert.bsky.social
It was such a joy working with @samuelbharti.com this summer. Absolutely insane what he was able to accomplish during his internship at @posit.co. Please give him a follow and check out this work if you're at all interested in shiny, bioinformatics, and genomics.

#rstats #pydata
samuelbharti.com Samuel Bharti @samuelbharti.com · 25d
Excited to share my latest blog on Posit Open Source!

During my internship, I built 10 apps and 5 computational biology packages using R, Python, Shiny, and Shinyreact to make scientific research more accessible, especially in rare diseases and cancer.

opensource.posit.co/blog/2026-10...
Genomes, Prompts, and Shiny: What I Built During My Summer at Posit
10 open-source applications and 5 packages for computational biology, built over a summer on the Shiny team, and the reusable layer that grew underneath them.
opensource.posit.co
October 14, 2026 at 12:33 AM
dslc.io
It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io!
#RStats #PyData #JuliaLang #RustLang #DataViz #DataScience #DataAnalytics #data #tidyverse #DataBS
October 13, 2026 at 7:25 PM
nocomplexity.bsky.social
Validating a Python file before processing it is a genuine challenge.
fileaudit is a simple, secure solution when your Python program processes or analyses Python files.
github.com/nocomplexity...

#python #infosec #pycon #pydata #owasp
GitHub - nocomplexity/fileaudit: Simplify building secure Python applications by default. Validate files before you use them.
Simplify building secure Python applications by default. Validate files before you use them. - nocomplexity/fileaudit
github.com
October 13, 2026 at 6:08 PM
pycon-nl.bsky.social
Organizers, this one’s for you 🤝

“What actually makes a Python community thrive?” — a 2-hour interactive session at PyCon NL, hosted by Gareth Thomas (chair of PyData Eindhoven).

No slides. You’re the experts.

15 October, Utrecht 🐍

#PyConNL #Python #Community
October 13, 2026 at 7:15 AM
jonthegeek.com
@dslc.io welcomes you to week 41 of #TidyTuesday! We're exploring AmphibiaWeb!

📂 https://tidytues.day/2026/2026-10-13
📰 https://onlinelibrary.wiley.com/doi/10.1002/ece3.73207

#RStats #PyData #JuliaLang #DataViz #tidyverse #r4ds
Logo for the #TidyTuesday Project. The words TidyTuesday, A weekly data project from the Data Science Learning Community (dslc.io) overlaying a black paint splash. TidyTuesday is a weekly social data project. All are welcome to participate! Please remember to share the code used to generate your results! TidyTuesday is organized by the Data Science Learning Community. Join our Slack for free online help with R and other data-related topics, or to participate in a data-related book club! How to Participate Data is posted to social media every Monday morning. Follow the instructions in the new post for how to download the data. Explore the data, watching out for interesting relationships. We would like to emphasize that you should not draw conclusions about causation in the data. Create a visualization, a model, a shiny app, or some other piece of data-science-related output, using R or another programming language. Share your output and the code used to generate it on social media with the #TidyTuesday hashtag. A broad phylogenetic family tree diagram for Class Amphibia produced by AmphibiaWeb. The tree branches into three major color-coded orders radiating from a shared ancestor: Gymnophiona (caecilians) in purple at the top, Caudata (salamanders and newts) in orange in the middle section, and Anura (frogs and toads) forming the largest green clade along the bottom. Individual taxonomic families and key clades are labeled at the tips of each branch, illustrating the evolutionary relationships and relative family diversity across the three amphibian orders. A four-panel scientific grid analyzing amphibian diversity in Central Africa against distance from historical Pleistocene forest refugia in kilometers. Panel A plots species richness, showing a strong negative linear relationship (R-squared = 0.71) where species richness decreases significantly as distance from historical refugia increases. Panel B plots phylogenetic diversity, displaying a matching steep negative trend (R-squared = 0.75). Panel C plots relative phylogenetic diversity with a moderate negative trend (R-squared = 0.56). Panel D plots phylogenetic endemism, showing a weak relationship (R-squared = 0.09). Each panel features a spatial map of Central Africa above its scatter plot, illustrating highest species concentration clustered directly within historical forest refugia zones.
October 12, 2026 at 8:18 PM
esciencecenter.bsky.social
But RS-DAT isn’t limited to earth observation! Checkout our project website: hpc-dat.github.io for the dates of upcoming introductory workshops and bring-your-own-problem hackathons. We’ll be finalising dates for the end of 2026 shortly.
HPC-DAT | Research computing without the barrier
HPC-DAT lowers the technical barrier to high-performance computing for researchers working with Python, PyData, Jupyter, and Dask.
hpc-dat.github.io
October 10, 2026 at 3:03 PM
nocomplexity.bsky.social
Keep Your Secrets Safe: Modern Practices for Python Code

Never ever use the python dotenv-project or .env files for managing secrets in Python applications!

medium.com/@maikelmardj...

#Python #cybersecurity #infosec #pydata #secrets
How To Use Secrets in Python Code
Keep Your Secrets Safe: Modern Practices for Python Code
medium.com
October 8, 2026 at 7:19 PM
madrid.pydata.org
🚀 Wednesday at 6:30PM: ⚙️ Construcción de un AI Hub y explorando la IA...

¡Ven a charlar sobre Python y datos! 🐍 No olvides la regla del comecocos. ✨
Aprenderemos sobre sistemas multiagente y el uso de AutoGuardrails. 🤖🚀

Check it out 👉 https://guild.host/e-zs3u2b
⚙️ Construcción de un AI Hub y explorando la IA abierta de Santander
PyData Madrid vuelve el 14 de octubre para hablar de Python, datos e inteligencia artificial, ¡Y lo que surja! Este mes nos reuniremos en la sede de Bain (Calle Velázquez, 86d) que generosamente nos cede su espacio. Tendremos el placer de contar con dos charlas, ambas en español: Pablo Rodríguez Pérez (Lead Data Scientist @ Bain): "Construcción de un AI Hub". Recorreremos el desarrollo de una plataforma multiagente: desde las primeras iteraciones hasta una arquitectura de agentes independientes conectados. Luis Ibáñez-Lissen y Pablo Delgado (Santander AI Lab / Santander Data and Science): "Open Source en IA de Santander". Presentarán algunas de las iniciativas para construir soluciones de IA abiertas, reutilizables y responsables. Entre ellas, mostrarán AutoGuardrails, una iniciativa de SantanderAI, y otros proyectos orientados a impulsar arquitecturas de IA más abiertas y resilientes. Después del evento, nos quedaremos haciendo networking por la zona. Recomendaciones generales: ¿Sabes mucho de Python y datos? ¿Sabes poco y quieres aprender más? ¡En ambos casos, te damos la bienvenida! Aplica la «regla del comecocos»: si estás en un círculo, deja siempre un hueco para que otra persona se pueda unir. Puede haber asistentes que no hablen bien español y se manejen mejor en inglés. Ten paciencia y ¡no dejes que se aburran! En los eventos PyData rige un Código de Conducta. En resumen: sé amable, abstente de insultar o hacer bromas sexistas, racistas o excluyentes, y evita cualquier insinuación sexual hacia otras personas. [ENG] PyData Madrid returns on October 14 to talk about Python, data, artificial intelligence, and whatever else comes up! This month, we will meet at Bain’s offices ([Calle Velázquez,
guild.host
October 8, 2026 at 9:41 PM
dslc.io
It's #TidyTuesday y'all! Show us what you made on our Slack at https://dslc.io!
#RStats #PyData #JuliaLang #RustLang #DataViz #DataScience #DataAnalytics #data #tidyverse #DataBS
October 6, 2026 at 6:32 PM