rbtl - Data communication

Lars Schöbitz

Global Health Engineering - ETH Zurich

2022-06-02

Today

  1. Part 1: Exam advice and practice
    • Programming exercise
  2. Part 2: Data communication
    • Live Coding Exercise
  3. Part 3: What comes next?
  4. Part 4: Evaluation
  5. Part 5: Individual work and questions

Learning Objectives

  1. Learners can use R Markdown Quarto and GitHub to publish their group project a report.

  2. Learners can use exported references from Zotero in Better BibTex Format to generate an automated reference list. Assignment 3 - YouTube Video - 13:58

  3. Learners can cross-reference figures and tables within an R Markdown file.

Part 1: Exam advice and practice

Bookmarks

Screenshot a bookmarks toolbar with a folder for RStudio Cloud projects.

Timing

  • Room: IFW C42 (not our lecture room)
  • Doors open: 14:30 (also on Zoom)
  • Exam start: 15:15
  • Exam end: 17:15

Workflow

  • Open Projects page on RStudio Cloud rbtl-fs22 Workspace
  • Look for ‘exam-fs22’ assignment
  • Click ‘Start’
Screenshot of an RStudio Cloud assignment.

Workflow

  • Briefly read through each section at the beginning to see what’s coming
  • 20 tasks coding tasks in four sections
  • Points for each task are shown
  • Work through the sections
.
├── README.md
├── data
│   └── what_a_waste
├── exam-fs22.Rproj
├── section-01.qmd
├── section-02.qmd
├── section-03.qmd
└── section-04.qmd

Workflow

  • No cloning repositories in this exam
  • No commits during the exam time (one commit after the exam time ends)
  • No pushing to GitHub in this exam

Rules

  • Headphones (music) allowed
  • Stick Notes or raised hand for support (no loud calling)
  • No talking with each other
  • Individual work (0 points of code is shared)

Practice Exam

ae-15-data-communication

  1. Head over to the GitHub Organisation for the course.
  2. Find the repo for week 15 that has your GitHub username.
  3. Clone the repo with your username to the RStudio Cloud.
  4. Open the file: ae-15a-communicate.qmd
  5. Use your Sticky Notes to let me know when you are ready.

Work through the tasks

25:00

Step-wise points

ggplot(data = waste_data_long_mean, 
       mapping = aes(x = mean_percent, 
                     y = waste_category, 
                     fill = income_cat)) + # 1
  geom_col(position = position_dodge()) + # 1
  labs(title = "Waste Composition", # 0.5
       subtitle = "Mean percentages ...", # 0.5
       x = "mean (percent)", # 0.5
       y = "waste category", # 0.5
       fill = "Income category", # 0.5
       caption = "Data from: ...") + # 0.5
  scale_x_continuous(breaks = seq(0, 50, 5)) + # 1
  scale_fill_brewer(type = "qual", palette = 3) + # 1
  theme_minimal() + # 0.5
  theme(panel.grid.minor = element_blank(), # 0.5
        panel.grid.major.y = element_blank()) # 0.5

What to study?

  • Practice writing code
  • All tasks are coding tasks
  • A small set of YAML header tasks
  • Nothing Git or GitHub related

Exam data

What a Waste

  • City level data
  • Repos for each of you in our GitHub Organisation
  • The repo starts with rbtl-fs22-exam-data
  • Clone it to RStudio Cloud and have fun! :)

Part 2: Data communication

What is Quarto?

  • Next generation version of R Markdown from RStudio
  • Multi-language (Python, R, Julia, Observable)
  • Authoring in plain text markdown or Jupyter notebooks

Editing documents

You’re not limited to RStudio for editing Quarto documents…

Authoring

  • Technical articles, reports, presentations, websites, blogs, and books in HTML, PDF, MS Word, ePub, and more.

  • Author with scientific markdown, including equations, citations, crossrefs, figure panels, callouts, advanced layout, and more.

Documentation

Screenshot of the Quarto homepage at https://quarto.org/.

Break One

15:00

Live Coding Exercise

ae-15-data-communication

  1. Back to ae-15a-communicate.qmd

Captions and cross-references

  • no space between {r} and #| tbl-cap: "A table"
  • spelling tbl not tab
  • no spaces (use dashes in label)

See Table 1…

```{r}
#| tbl-cap: "A table"
#| label: tbl-simple-table

tibble(
  id = c(1, 2, 3),
  name = c("X", "Y", "Z")
) %>% 
  knitr::kable()
```
Table 1: A table
id name
1 X
2 Y
3 Z

Part 3: What comes next?

Research Project Report

  • Due date: 9th of June 23:59
  • No commits after that point will be accepted

rbtl community meetup events

  • every two months
  • ~1 hour code-along, followed by Apéro
  • in-person and remote on Zoom
  • first topic suggestions:
    • Get out of the Cloud!
    • Dashboards

Break Two

10:00

Part 4: Evaluation & Reflection

Write up some notes

  • What are the three most useful things you learned?
  • Which topic was especially hard to follow?
  • What did you miss?

rbtl evaluation

  • 5 mins
  • anonymous
  • after each lecture

kutt.it/rbtl-eval

ETH evaluation

  • You received an Email from ETH LET
  • Please take 30 minutes now to complete the survey
  • If you have completed the survey already, then you can use your time freely now

Part 5: Individual work and questions

Thanks! 🌻

Slides created via revealjs and Quarto: https://quarto.org/docs/presentations/revealjs/ Access slides as PDF on GitHub

All material is licensed under Creative Commons Attribution Share Alike 4.0 International.