Welcome & get ready for the course

ds4owd - data science for openwashdata

Lars Schöbitz

ETH Zurich

Sep 11, 2025

Email from GitHub?

While we are getting ready, please check for this email from GitHub and accept the invitation to join the GitHub organisation for the course. Used Gmail to sign up? Check the folders that aren’t your primary inbox (e.g Updates).

Welcome!

Meet the team

Lars Schöbitz

• Env. Engineer
• retired WASH Researcher
• RStudio certified instructor

Adriana Clavijo

• Data Scientist
• Spanish language support
• Technical Support

Nicolò Massari

• Research Software Engineer
• Computational Physicist
• Technical Support

Overall Goals (for the course)

1. Master data science tools - Use (R, RStudio IDE, Git, GitHub, tidyverse, Quarto) to analyze and communicate data effectively.

2. Create reproducible documents - Produce professional reports with Quarto, including citations, figures, and tables.

3. Practice open science - Share your data and code openly, following best practices for reproducibility and collaboration.

4. Build a portfolio - Complete real-world projects that demonstrate your skills to future employers or collaborators.

Your turn: About you

Pick an item and take notes for 1 minute:

What does the item you have picked have to do with the reason for you being here?

01:00

In break-out rooms

Take 1 minute each to share with your room partner:

What does the item you have picked have to do with the reason for you being here?

05:00

Course Calendar

date	week	topic	module
11 September 2025	1	Welcome & get ready for the course	module 1
18 September 2025	2	Data science lifecycle & Exploratory data analysis using visualization	module 2
25 September 2025	3	Data transformation with dplyr	module 3
02 October 2025	4	Data import & Data organization in spreadsheets	module 4
09 October 2025	5	No class	NA
16 October 2025	6	No class	NA
23 October 2025	7	Conditions & Dates & Tables	module 5
30 October 2025	8	Data types & Vectors & For Loops	module 6
06 November 2025	9	Pivoting & joining data	module 7
13 November 2025	10	Creating and publishing scholarly articles with Quarto and GitHub pages	module 8
20 November 2025	11	Bonus module: Use of AI for coding support	module 9
27 November 2025	12	Work on Capstone project	NA
04 December 2025	13	Work on Capstone project	NA
11 December 2025	14	Final submission date of Capstone project	NA
18 December 2025	15	Graduation of openwashdata academy	module 10

Course structure

• My turn: Lecture segments + live coding
• Our turn: Live coding + follow along
• Your turn: Exercises in break-out rooms

My turn: Lecture segments + live coding

• Instructor writes and narrates code out loud
• Instructor explains concepts and principles that are relevant
• Learners do not join, but rather watch and listen
• Learners are welcome to ask questions in the Zoom chat

Our turn: Live coding + follow along

• Instructor writes and narrates code out loud
• Instructor explains concepts and principles that are relevant
• Ideally, learners display their coding window on a second screen
• Learners join by writing and executing the same code

Your turn: Exercises in break-out rooms

• Two to four learners work together in a break out session
• One person (the driver) shares the screen and does the typing
• The other persons (the navigator) offers comments and suggestions and write on their own

Getting help

• During my turn and our turn segments: Please keep your microphone on mute. Send a message to the Zoom chat, Adriana and Nicoló will support you

• During your turn segments: Due to the large number of participants, it will not be feasible to join individual break-out rooms, but you will hopefully always be working in groups of 2 to 4 people.

Platforms and Tools

• R
• tidyverse R Packages
• Posit Cloud
• RStudio IDE
• Quarto publishing system
• Element

Course website

Bookmark this page in your browser

ds4owd-002.github.io/website/

Learning Objectives (for this week)

1. Learners can access the Posit Cloud workspace for the course.
2. Learners can use the Element chat to introduce themselves.
3. Learners can open an issue on GitHub and tag the course instructor.
4. Learners can clone a repository from GitHub and use the GitHub PAT to push a commit from their local repository to GitHub.

Artwork from @juliesquid for @openscapes (illustrated by @allison_horst)

Posit Cloud

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Screen setup - Poll

One computer screen

Two or more computer screens

Hello Quarto

Meeting you where you are

I’ll assume you

• do not have R or git experience

• have not worked in an IDE before (e.g. RStudio IDE)

• want to learn about R

• want to learn about Quarto and publishing

• want to learn about project management with GitHub

I’ll teach you

• R

• Quarto syntax and formats

• Markdown

• Git via RStudio GUI

• GitHub issues, project management, and publishing

Learner profile

Programming experience

192 registrations on pre-course survey.

What is Quarto?

Quarto …

• is a new, open-source, scientific, and technical publishing system
• aims to make the process of creating and collaborating dramatically better

Artwork from “Hello, Quarto” keynote by Julia Lowndes and Mine Çetinkaya-Rundel, presented at RStudio Conference 2022. Illustrated by Allison Horst.

My turn: A tour of Quarto

Sit back and enjoy!

Your turn: Log into Posit Cloud with GitHub account

• Go to the Posit Cloud Sign Up page: login.posit.cloud/register
• Click on the Sign Up with GitHub button.
• Enter your GitHub username and password when prompted.
• Open and accept the workspace invitation (Link is in the Zoom chat now).
• Bookmark the address of the open tab in your browser.

GitHub Authorisation

• If this is your first time logging in to Posit Cloud with your GitHub account, you will be prompted to authorize Posit Cloud to access your GitHub account information.
• Once you have authorized access, you will be redirected back to the Posit Cloud website and logged in to your account.

https://posit.cloud/spaces/663318/join?access_code=8IiLL7Fi5kH6ElaW8G8njVf5kseZab61yqFMpnPu

08:00

Take a break

Please get up and move!

10:00

Photo by Blake Wisz

Your turn: md-01-exercises

1. Open posit.cloud/spaces/663318/content in your browser.
2. If you are not in the ds4owd-002 workspace, open it.
3. Click Start next to md-01-exercises.
4. In the File Manager in the bottom right window, locate the hello-quarto.qmd file and click on it.
5. Click the Render button to render the document. You may need to allow pop-ups in your browser.
6. In the YAML header, at the author: key replace Your Name with your name.
7. Render the document again.
8. Inspect components of the document and make one more update and re-render.
9. Discuss notes about updates you’ve made with your room partners.

10:00

From the comfort of your own workspace

Quarto formats

One install, “Batteries included”

• RMarkdown grew into a large ecosystem, with varying syntax.

• Quarto comes “batteries included” straight out of the box

  • HTML reports and websites
  • PDF reports
  • MS Office (Word, Powerpoint)
  • Presentations (Powerpoint, Beamer, revealjs)
  • Books

• Any language, exact same approach and syntax

Many Quarto formats

Feature	R Markdown	Quarto
Basic Formats	html_document pdf_document word_document	html pdf docx
Beamer	beamer_presentation	beamer
PowerPoint	powerpoint_presentation	pptx
HTML Slides	xaringan ioslides revealjs	revealjs
Advanced Layout	tufte distill	Quarto Article Layout

Many Quarto formats

Feature	R Markdown	Quarto
Cross References	html_document2 pdf_document2 word_document2	Quarto Crossrefs
Websites & Blogs	blogdown distill	Quarto Websites Quarto Blogs
Books	bookdown	Quarto Books
Interactivity	Shiny Documents	Quarto Interactive Documents
Journal Articles	rticles	Journal Articles |
Dashboards	flexdashboard	Quarto Dashboards |

Your turn: Create a new Quarto document

In your md-01-exercises project on Posit Cloud, go to File > New File > Quarto document to create a Quarto document with HTML output.

• Render the document, which will ask you to give it a name: you can use my-first-document.qmd.

Use the visual editor for the next steps.

• Add a title and your name as the author.

• Create four sections with headings of level 2 (Introduction, Methods, Results, Conclusions).

• Stretch goal: Change the html theme to sketchy. Tipp: Check quarto.org and use search function with “HTML theming”

15:00

Version Control

Version Control with Git and GitHub

A way to share files with others, so they can:

• download
• re-use
• contribute

You can view the history of files, and jump back in time to any point.

Why is it useful?

Git and GitHub

• Git is a software for version control
• Created in 2005
• Popular among programmers collaboratively developing code
• Tracks changes in a set of files (directory/folder/repository)

• GitHub is a hosting platform for version control using Git

• Launched in 2008, aquired by Microsoft in 2018 for US$ 7.5 billion

• 100 million Users (20.5 in 2022 alone) (October, 2023)

• Social media for software developers

My turn: A tour of GitHub

Sit back and enjoy!

Your turn: Create an issue on GitHub

1. Open github.com in your browser and login with your credentials
2. Exchange your GitHub username with your room partner by adding it into the Zoom chat.
3. Find and open the md-01-issue repository
4. Find the issue tracker (Issues tab) on the top menu bar
5. Click on New issue to create a new issue
6. Add the title “My first issue on GitHub”
7. Add one of your room partners to the list of Assignees on the right panel by clicking on the gear icon and searching their username.
8. Add a comment to the issue and tag Adriana @seawaR, Nicoló @massarin, and Lars with @larnsce.
9. Click Create to add the new issue.
10. Check if you have received a notification about the new issue (Email or Notifications Inbox in the top-right corner on github.com).
11. Open the issue you are tagged in and respond to the comment of your room partner.

10:00

Take a break

Please get up and move! Let your emails rest in peace.

10:00

Photo by Blake Wisz

Anatomy of a Quarto document

Components

1. Metadata: YAML

2. Text: Markdown

3. Code: Executed via knitr or jupyter

Weave it all together, and you have beautiful, powerful, and useful outputs!

Literate programming

Literate programming is writing out the program logic in a human language with included (separated by a primitive markup) code snippets and macros.

---
title: "ggplot2 demo"
date: "5/23/2023"
format: html
---

## MPG

There is a relationship between city and highway mileage.

```{r}
#| label: fig-mpg

library(ggplot2)

ggplot(mpg, aes(x = cty, y = hwy)) + 
  geom_point() + 
  geom_smooth(method = "loess")
```

Source: https://en.wikipedia.org/wiki/Literate_programming

Metadata

YAML

“Yet Another Markup Language” or “YAML Ain’t Markup Language” is used to provide document level metadata.

---
key: value
---

Output options

---
format: something
---

---
format: html
---

---
format: pdf
---

---
format: revealjs
---

Output option arguments

Indentation matters!

---
format: 
  html:
    toc: true
    code-fold: true
---

YAML validation

• Invalid: No space after :

---
format:html
---

• Invalid: Read as missing

---
format:
html
---

YAML validation

There are multiple ways of formatting valid YAML:

• Valid: There’s a space after :

format: html

• Valid: format: html with selections made with proper indentation

format: 
  html:
    toc: true

R fundamentals

Packages

base R

sqrt(49)
sum(1, 2)

• Functions come with R

R Packages

library(dplyr)

• Installed once in the Console: install.packages("dplyr")
• Loaded per script

Packages

• Main way that reusable code is shared in R
• Combination of code, data, and documentation
• R has a rich ecosystem of packages for data manipulation & analysis

Functions & Arguments

library(dplyr)

filter(.data = gapminder, 
       year == 2007)

• Function: filter()
• Argument: .data =
• Arguments following: year == 2007 What do do with the data

Functions & Arguments

library(dplyr)

filter(gapminder, year == 2007)

• Function: filter()
• Argument: .data = Does not need to be be spelled out
• Arguments following: year == 2007

Objects

library(dplyr)

gapminder_yr_2007 <- filter(gapminder, year == 2007)

• Function: filter()
• Argument: .data =
• Arguments following: year == 2007
• Assignment operator: <- Assigns the result to an object
• Object: gapminder_yr_2007 Name of the object that stores result

Operators

library(dplyr)

gapminder_yr_2007 <- gapminder |> 
  filter(year == 2007) 

• Function: filter()
• Argument: .data =
• Arguments following: year == 2007
• Object: gapminder_yr_2007
• Assignment operator: <-
• Pipe operator: |> Passes the result into the first argument of the next function

Rules

Rules of dplyr functions:

• First argument is always a data frame
• Subsequent arguments say what to do with that data frame
• Always return a data frame
  
• Don’t modify in place

Does this look and sound foreign and confusing?

These concepts will be repeated many times

We’ll revisit these R fundamentals throughout the next 9 weeks:

• Week by week, we’ll build on these concepts gradually
• Practice will help - you’ll see these patterns repeatedly
• No need to memorize - understanding will come with practice

You’re not expected to remember or fully understand everything right now. This is your first exposure!

Course information

Weekly Structure

Monday
Tuesday	Office hours on Zoom (2 pm to 3 pm CET)
Wednesday	Homework due
Thursday	Module from 2 pm to 4:30 pm CET
Friday

Homework assignments

• Weekly assignments (module 1 homework is required for participation)
• Homework assignment due Wednesdays before next module
• Quiz due one week after homework assignment and required for successful completion of the course
• Submitted as rendered Quarto documents on GitHub
• Reviewed by course instructors
• Management and support through GitHub issue tracker

Capstone Project

• Data analysis project report with a dataset of your choice
• Submitted as rendered Quarto document on GitHub
• Submission required for successful completion of the course

Homework assignments module 1

Module 1 documentation

ds4owd-002.github.io/website/content/modules/md-01.html

Homework due date

• Homework assignment due: Wednesday, 2025-09-17
• Quiz due: Wednesday, 2025-09-24

Wrap-up

Thanks!

Slides created via revealjs and Quarto: https://quarto.org/docs/presentations/revealjs/

Access slides as PDF on GitHub