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@dslc.ioOct 9, 2026, 12:56 PM

Recent DSLC.club meetings:

🔵 R4DS: Strings youtu.be/7T-r3MzcbPg

From the DSLC.video aRchives:

🔵 Mastering Shiny: Escaping the graph youtu.be/M4cOIFbBNfQ

Support the Data Science Learning Community at patreon.com/DSLC

#dataBS #RStats #R4DS

@jonthegeek.comOct 5, 2026, 7:38 PM

@dslc.io welcomes you to week 40 of #TidyTuesday! We're exploring Avocado Oil Authenticity!

📂 https://tidytues.day/2026/2026-10-06
📰 https://www.ucdavis.edu/food/news/avocado-oil-chip-youre-eating-may-not-be-made-pure-avocado-oil

#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.PCA biplot of fatty acid profiles from oils extracted from processed foods. Samples classified as consistent with authentic avocado oil cluster together on the right, clearly separated from inconsistent samples that cluster near vegetable oil comparators on the left, demonstrating that chemical fingerprinting can reliably distinguish authentic avocado oil from adulterated products.
@dslc.ioSep 30, 2026, 1:17 PM

Recent DSLC.club meetings:

🔵 R4DS: Numbers youtu.be/b6Q7UfReAuY

From the DSLC.video aRchives:

🔵 Advanced R: Functions - part I youtu.be/UD4DCDuUpg0

Support the Data Science Learning Community at patreon.com/DSLC

#dataBS #RStats #R4DS

@jonthegeek.comSep 28, 2026, 6:48 PM

@dslc.io welcomes you to week 39 of #TidyTuesday! We're exploring Health metrics in urban centres worldwide!

📂 https://tidytues.day/2026/2026-09-29
📰 https://human-settlement.emergency.copernicus.eu/ghs_ucdb_2024.php

#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.Exterior of a modern hospital building at dusk, with a brick and glass facade lit from within, a colorful sculpture of a child holding balloons on the wall, young trees and a landscaped walkway in front, and a U.S. flag near the entrance. Photo by Acton Crawford on Unsplash, https://unsplash.com/photos/brown-and-white-concrete-building-near-green-trees-under-blue-sky-during-daytime-8PB_TFEy2XQ
@jonthegeek.comSep 23, 2026, 1:42 PM

@dslc.io welcomes you to week 38 of #TidyTuesday! We're exploring Average share of green areas across cities!

📁 https://tidytues.day/2026/2026-09-22
📰 https://data.unhabitat.org/pages/open-spaces-and-green-areas

#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 map of the world, with each country colored in shades of yellow-green by the average share of urban area that is green, by country in 2020. Portugal, Belize, and Fiji appear to be the most green at about 25-30% green in urban areas.
@dslc.ioSep 23, 2026, 11:53 AM

Recent DSLC.club meetings:

🔵 R4DS: Logical vectors youtu.be/BWOGoTTqFzQ

From the DSLC video aRchives:

🔵 R for Data Science: Joins youtu.be/O57XwU3Erus

Support the Data Science Learning Community at patreon.com/DSLC

#dataBS #RStats #R4DS

@dslc.ioSep 17, 2026, 12:14 PM

Recent DSLC.club meetings:

🔵 R4DS: Communication youtu.be/FtXyZR2leSY

From the DSLC.video aRchives:

🔵 R for Data Science: Workflow: code style youtu.be/10wZX5UnpO4

Support the Data Science Learning Community at patreon.com/DSLC

#dataBS #RStats #R4DS

@jonthegeek.comSep 14, 2026, 4:58 PM

@dslc.io welcomes you to week 37 of #TidyTuesday! We're exploring Dead Sea Scrolls Manuscripts!

📂 https://tidytues.day/2026/2026-09-15
📰 https://www.deadseascrolls.org.il/

#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.Bar chart showing manuscript copy counts by biblical book, with deuterocanonical books highlighted in orange alongside protocanonical books in blue.
@dslc.ioSep 14, 2026, 1:27 PM

From the DSLC.video aRchives:

🔵 Learning Statistics with R: Why do we learn statistics? youtu.be/RGFQ7IaBv50

🔵 R for Data Science: Data transformation youtu.be/xxzKKWVoNOA

Support the Data Science Learning Community at patreon.com/DSLC

#dataBS #RStats #statistics #R4DS

@sponce1.bsky.socialSep 7, 2026, 6:40 PM

📊 #TidyTuesday – 2026 W36 | The Cappuccino Index
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🔗: stevenponce.netlify.app/data_visuali...
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#rstats | #r4ds | #dataviz | #ggplot2

Scatter plot titled "Cheap coffee isn't necessarily affordable coffee," plotting mean hourly barista wage against mean cappuccino price across 87 countries on log-log axes, with dashed diagonal lines marking equal work-time cost at 30, 60, and 120 minutes. Pakistan (£1.87 cappuccino, 277 minutes of work) and India (£1.96, 172 minutes) sit far left with cheap coffee but extreme work-time burdens driven by very low wages. Switzerland and Denmark, both averaging £5.41 per cappuccino, require only 14 and 19 minutes, respectively, reflecting high wages. The remaining gray points cluster loosely along the diagonal. Source: James Hoffmann via Filip Reierson.
@jonthegeek.comSep 7, 2026, 4:26 PM

@dslc.io welcomes you to week 36 of #TidyTuesday! We're exploring The Cappuccino Index!

📁 https://tidytues.day/2026/2026-09-08
🗞️ https://www.youtube.com/watch?v=WtlE3BW9Nqs

#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.Coffee beans.