Here we are 👉🗺️ the final day of #30DayMapChallenge 2025 💛
30 maps, 30 ideas — exploring data, design, projections, rasters, OSM layers, insets, palettes & reproducible R workflows.
Improved something new every day. 💛
#RStats#GIS#DataViz#Geospatial#Quarto
📚 New issue — Notes on Data and Learning N.24
Learning R isn't just memorizing functions. With AI automating code, the crucial skill is understanding workflows — how data, code, docs, and decisions connect.
Read: https://t.co/6E5ffM5ymX
#RStats#DataScience#AI
New issue out ✍️
Notes on Data and Learning — N.23
When Priorities Choose Themselves
This week was supposed to be about organization.
Continue Reading: https://t.co/6E5ffM5ymX
📢 Upcoming R-Ladies Rome Workshop
From Data Analysis to Publication: Reproducible Research with R and Quarto
🎙️ With Betsabé Cohen & Jesica Formoso (R-Ladies+ Buenos Aires)
📅 Registration: https://t.co/0PXNXMcDpH
#RLadiesRome#RStats#QuartoPub#ReproducibleResearch
New issue published.
Notes on Data and Learning — N.20
Learning Structure: Notes, Graphs, and the Coordination of Uncertainty
This week I wrote about Obsidian and Ebola. How much structure is enough to preserve reasoning without creating noise?
Read More: https://t.co/6E5ffM5ymX
New issue of Notes on Data and Learning published:
N.19 — The Geometry of Coordination
This week’s reflection started from an unexpected place: the strange way ideas continue moving after a project is technically “finished.”
Continue Reading https://t.co/6E5ffM5ymX
🦠 Questa Domenica terrò un incontro online in italiano su Hantavirus, epidemiologia e diffusione delle infezioni negli ambienti chiusi e connessi.
🎁 Giveaway di 1–2 copie del mio libro.
🔗 https://t.co/7n5LYXV7YM
📅 Domenica
🕡 17:00
💻 Online
#Hantavirus#SalutePubblica
New R-Hack published: Your Script Is Not a Workflow
The problem often appears only later, when the session is restarted and the analysis depends on objects, steps, or assumptions that were never made explicit.
👉 Read the full issue here: https://t.co/QD7ImpAMMO
New issue published:
Notes on Data and Learning — N.18
From Workflows to Coordination: The Power of Direct Access
AI responds to structure.
Humans respond to meaning, emotion, timing, and willingness.
Read More: https://t.co/6E5ffM5ymX
#AI#MCP#LLM#AgenticAI#HumanAI
New R-Hack published: Stop rewriting the same code
A lot of R workflows don’t become difficult because they are complex. AI makes it easy to generate code.
It also makes it easy to repeat the same logic over and over.
👉 https://t.co/anN3MEULrX
#rstats
Issue N.17 — Learning Control
Getting a system to work is not the hard part.
Keeping it under control as conditions change is.
AI follows instructions.
Humans don’t always.
→ https://t.co/6E5ffM5ymX
New R-Hack: Start learning R faster
Most people try to learn everything at once.
That’s where it slows down.
Start with one workflow.
Repeat it.
Build from there.
👉 https://t.co/fZis6oOjXm
#rstats#DataScience
Issue N.16 — From Prompts to Context
Same prompt. Different outputs.
The difference was context.
AI is shifting from prompt design → context design.
Read → https://t.co/6E5ffM5ymX
🔥 Reminder: our next @RLadiesRome session is coming up
“The Roots of AI: NLP and N-gram Models in R”
We’ll build a next-word prediction model from scratch
Data → counts → probabilities → prediction
See you there 👇 https://t.co/xRl5JTwypU
Issue N.15 — Learning to Prioritise
Working more ≠ progressing more.
The real constraint is attention, not time.
Starting is easy.
Staying with one task long enough to make it coherent is not.
Read → https://t.co/6E5ffM5ymX
New R-Hack: Stop guessing why your code breaks
Most people don’t debug.
They regenerate.
Small shift:
break the pipeline → find the failure
Read:
👉 https://t.co/fZis6oOjXm
#rstats#datascience#AI
New R-Hack: Validate AI-Generated Data Before Using It
AI can generate datasets in seconds, but they aren’t ready to use. Simple habit: validating AI-generated data before analysis.
👉 Read the full issue here: https://t.co/anN3MEULrX
More R-Hacks soon.
📘 Issue N.14 is out
Learning Structure: From JSON to Video Tutorials
Working with automation this week.
Even when AI helps generate JSON, understanding it remains essential.
👉 Full issue here: https://t.co/6E5ffM5ymX
New R-Hack published: n-grams in R — a small idea behind language models
Ahead of our next R-Ladies Rome session, this short post gives the intuition.
Read:
👉https://t.co/fZis6oOjXm
Join:
👉 https://t.co/xRl5JTwypU
#rstats#datascience#NLP#MachineLearning#AI