A proposta é conduzir os participantes por **quatro perspectivas complementares**:

1. **Dados** – entender a qualidade, estrutura e contexto do conjunto de dados antes de qualquer visualização.
2. **Exploração** – experimentar opções gráficas e análises para descobrir padrões e relações.
3. **Explanação** – escolher formas de apresentação que tornem a informação clara, atraente e adequada ao público.
4. **Narrativa** – conectar tudo em uma história que engaje, sem perder a precisão.

O objetivo é ir além do chamado *data storytelling* tradicional, mostrando que comunicar bem exige atenção desde a preparação dos dados até a construção da narrativa final. É um curso que une fundamentos de visualização (como o uso do **ggplot** no R) a decisões de design e de storytelling, ajudando quem trabalha com dados a transformar análises em mensagens realmente impactantes.

Nos siga nas redes sociais: @rladiesgyn
#VemAí #MistérioNoConsole

R-Ladies Goiânia

Fernanda Kelly

Edleide Brito

Rhobis

Fabiano Bueno

wanessa.a.lima

Claudinha Costa

Andrielly

sara teixeira

ludmilanaud

Aline Pôrto

Wanessa Alves Lima

Suzi Sayuri

Henrique Aguilar

Tiago santos da silva Silva

Juliana Campbell

Joao Paiva

Ana Caroline de Souza Santos

Comunicação efetiva com dados: da exploração à explanação

Online event

Our October Meetup will be a remote gathering; the Zoom link will be posted the week before the event.

From our speaker:
"I think the highest value skillset in statistical programming is knowing how to write good functions. Functions are often taught as a tool to avoid repetition using the mnemonic DRY: Don't Repeat Yourself. Whilst DRY is both true and real, I think functions are at their best when they encapsulate expression and are easy to reason with. That is, DRY is sufficient, but not necessary. Writing good functions is more than esoteric aesthetics. We need to be able to reason with our code in statistics. We often don't have the capacity to write tests to show our code is 'correct'. Instead, we need to rely on our ability to reason with, trust, and verify that the code works as it should. I believe writing good functions that encapsulate expressions and are able to be reasoned with are how we can ensure our code, and therefore our methods, and our analyses, work as they should. In this talk I will discuss some practical ideas on writing a good function, how to identify bad ones, and how to move between the two states."

Salt Lake City R Users Group

Andrew Redd

Julia Silge

Darren Triplett

Dan Nguyen

PriyankaGagneja

Brittany Blankinship

Jessica Linford

Wahab Moussa

Mary A

Akila B

DDeHaas

Jonathan Spring

Gustavo Pino

DeVerne Coleman

Gregers Kjerulf Dubrow

Orville Dulay Hombrebueno

Antonio H.

Sebastian Bauch

christel

António Cruz

Practical Functions, Practically Magic

Heard of Random Forests and aren’t sure where to start? Or have you always wanted to apply machine learning to a problem but are worried about the ‘black box’ nature of the models? This talk will introduce one of the most interpretable and accessible machine learning algorithms, Random Forests. Beginning with a straightforward description of the model’s structure, this talk will then cover everything you need to start running your own Random Forest models in R: from data preparation, variable selection, and types of Random Forest models – to plotting and interpreting outputs and accuracy measures. By the end of the session, you’ll be branching out into machine learning with confidence!

R User Group at the University of Manchester

RUM University of Manchester

Chidinam Lynda Akaihe

Muloogi Derick

Md Monzurul Karim

Weijie Liu

Abdur-Rahman

J Hodgetts

Samrit Pramanik

sarlathawre

Harry Young

Adriana

Ryan Smyth

Jason Kennedy

oskar holm

Çiğdem

David Gardner

Benjamin Ohana

Marylène Henry

Can’t see the forest for the trees? An intro to Random Forest ML in R

GA.056 Nancy Rothwell Building, University of Manchester

We look forward to this year’s autumn edition of the Zurich R User Meetup, which is all about mobility!
The meetup will take place at the main building of the University of Zurich ([KOL-H-317](https://www.uniability.uzh.ch/static/current/buildings/KOL/), Rämistrasse 71, 8006 Zürich).

\*\*\*\*
*Schedule:*
06.15 pm Doors open
06.30 pm Introduction / Welcome by the organizing team
06.40 pm Talks (see below)
ca 07.40 Take the Stage: Pitching job ads, ideas, events, ...
ca 08.00 - 09.00 pm Apéro
\*\*\*\*

*Samuel Wittwer: Data Analyst, Data and Mobility Analysis - Verkehrsbetriebe Zürich (VBZ)*

**R at the Heart of VBZ Mobility**

"VBZ has made substantial investments in its data analytics infrastructure, with R playing a central role in our modern, scalable ecosystem. Our internal platform now includes around 25 productive Shiny applications used by public transport companies in the entire ZVV area, and we continue to expand it step by step. As part of this evolution, I will present our user-centric development workflow, including our gradual transition of our shiny apps to use Bootstrap 5 for enhanced dashboard design and usability\*.\*"

\*\*\*\*

*Anna Reiffer: Post-Doctoral Researcher, ETH Zürich - Transportation and Mobility Planning*

**The R Roadmap for Mobility Behavior Analysis: From Surveys to Travel Choices and Accessibility**

"Household travel surveys are a goldmine for understanding how and why people move. In this talk I’ll share the R toolkit we use turn travel diaries, GPS traces, and spatial data into policy-ready insights and answer research questions in transport and mobility. Along the way
I’ll cover R packages for discrete choice modeling (e.g., to model mode choice), routing, network analysis, and accessibility estimation."

Zurich R User Group

Gerlinde

Minna Heim

Matt Bannert

Sereina Graber

Aurélien Sallin

Joëlle V

Patrick Schratz

Jasmin

Florian

Samuel Pawel

Jonas Theiler

Markus M

Matthias Bieri

Chi Zhang

Daniel Mastropietro

Jens Heumann 

Volodymyr

Erik-Jan Senn

Autumn Meetup: R in Mobility and TranspoRtation Analytics

Universität Zürich

## **Celebra el Día Internacional del Software de Investigación (#IntlRSEday) con la Comunidad de R**

El segundo jueves de octubre se celebra el Día Internacional del Software de Investigación (RSE Day, por sus siglas en inglés: Research Software Engineering).

Pero, ¿qué es exactamente RSE y qué tiene que ver el lenguaje R con el desarrollo de software para la investigación? Si te has hecho estas preguntas, ¡este evento es para ti!

Únete a nosotros el próximo 9 de octubre en este encuentro multi-comunidades, donde exploraremos el fascinante mundo de la Ingeniería de Software de Investigación.

**Importante**

* Para participar, seleccioná *"Asistiré"* en el evento y encontraras el link de zoom del evento.
* Recordá que al confirmar tu asistencia aceptás nuestro Código de Conducta [https://renbaires.github.io/coc.html](https://renbaires.github.io/coc.html)

### **🤝 Organizan**

### Este evento es una colaboración entre comunidades que impulsan el desarrollo de software y la ciencia abierta en Latinoamérica:

* R-Ladies Chile
* R-Ladies Resistencia-Corrientes
* R en Buenos Aires
* RSE Chile

R en Buenos Aires

Andrea Gomez Vargas

Ariana Bardauil

Emanuel Ciardullo

Gaston Becerra

renatorojasd96

Anabella Molina

Bernardo Eliezer

Eulios

albertalsinaferrando

Jesica Formoso

Mauro Crosignani

Charlamos sobre RSE en español: evento virtual por el #IntlRSEday ¡Sumate!

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