Quarto in 300 Seconds

Andrey Höglund

andrey.hoglund@aces.su.se

2026-06-29

Quarto is a software tool that . . .

• Interactive reports
• Computation inside the file!
• Written in Markdown format
• Inline code
• Open-source

viewof bins = Inputs.range([5, 100], {value: 30, step: 5, label: "Bins:"})

data = transpose(hist_data)

Plot.plot({
  marks: [
    Plot.rectY(data, Plot.binX({y: "count"}, {
      x: d => d.value,
      thresholds: bins,
      fill: "steelblue",
      stroke: "black"
    }))
  ],
  style: {background: "transparent", color: "white", fontSize: 18}
})

viewof species = Inputs.checkbox(
  ["setosa", "versicolor", "virginica"],
  {value: ["setosa", "versicolor", "virginica"], label: "Species:"}
)

idata = transpose(iris_data)
filtered = idata.filter(d => species.includes(d.Species))

colors = ({setosa: "steelblue", versicolor: "orange", virginica: "mediumseagreen"})

Plot.plot({
  marks: [
    Plot.boxY(filtered, {
      x: d => d.Species,
      y: d => d["Sepal.Length"],
      fill: d => d.Species,
      stroke: "black"
    })
  ],
  x: {label: "Species"},
  y: {label: "Sepal Length"},
  color: {range: ["steelblue", "orange", "mediumseagreen"]},
  style: {background: "transparent", color: "white", fontSize: 16},
  marginBottom: 40,
  marginLeft: 50
})

1. The Anatomy of a Quarto file

The Anatomy of a Quarto file

report_file.qmd

---
title: "Results!"
format: html
Author: "Andrey Höglund"
date: Today
---

# The results

The main results of the analysis were ...

```{r}
plot(1:10)
```

The Anatomy of a Quarto file

report_file.qmd

---
title: "Results!"
format: html
Author: "Andrey Höglund"
date: Today
---

# The results

The main results of the analysis were ...

```{r}
plot(1:10)
```

• YAML header (file’s meta data)

The Anatomy of a Quarto file

report_file.qmd

---
title: "Results!"
format: html
Author: "Andrey Höglund"
date: Today
---

# The results

The main results of the analysis were ...

```{r}
plot(1:10)
```

• YAML header (file’s meta data)
• Markdown

The Anatomy of a Quarto file

report_file.qmd

---
title: "Results!"
format: html
Author: "Andrey Höglund"
date: Today
---

# The results

The main results of the analysis were ...

```{r}
plot(1:10)
```

• YAML header (file’s meta data)
• Markdown
• code chunks

2. Running code inside a Quarto file

Running code inside a Quarto file

report_file.qmd

These code chucks will be executed with:

```{r}
# R
```

```{python}
# Python
```

```{julia}
# Julia
```

```{ojs}
# Observable
```

Running code inside a Quarto file

script.R

```{r}
# Air particle measurements in a vector
measurements <- c(10, 15, 20, 33, 50, 32, 49, 18, 30, 54, 23)
```

Quarto renders a file in the same manner as a jupyter notebook

Running code inside a Quarto file

script.R

```{r}
# Air particle measurements in a vector
measurements <- c(10, 15, 20, 33, 50, 32, 49, 18, 30, 54, 23)
length(measurements)
mean(measurements)
sum(measurements)
```

[1] 11

Quarto renders a file in the same manner as a jupyter notebook

Running code inside a Quarto file

script.R

```{r}
# Air particle measurements in a vector
measurements <- c(10, 15, 20, 33, 50, 32, 49, 18, 30, 54, 23)
length(measurements)
mean(measurements)
sum(measurements)
```

[1] 30.36364

Quarto renders a file in the same manner as a jupyter notebook

Running code inside a Quarto file

script.R

```{r}
# Air particle measurements in a vector
measurements <- c(10, 15, 20, 33, 50, 32, 49, 18, 30, 54, 23)
length(measurements)
mean(measurements)
sum(measurements)
```

[1] 334

Quarto renders a file in the same manner as a jupyter notebook

Running code inside a Quarto file

script.R

```{r}
# Air particle measurements in a vector
measurements <- c(10, 15, 20, 33, 50, 32, 49, 18, 30, 54, 23)
```

We collected `{r} length(measurements)` measurements.

The average was `{r} mean(measurements)`.

And the total sum was `{r} sum(measurements)`.

Inline code - do some calculation and present in the text

Running code inside a Quarto file

script.R

```{r}
# Air particle measurements in a vector
measurements <- c(10, 15, 20, 33, 50, 32, 49, 18, 30, 54, 23)
```

We collected `{r} length(measurements)` measurements.

The average was `{r} mean(measurements)`.

And the total sum was `{r} sum(measurements)`.

We collected 11 measurements.

The average was 30.3636364.

And the total sum was 334.

Inline code - do some calculation and present in the text

Running code inside a Quarto file

script.R

```{r}
# Air particle measurements in a vector
measurements <- c(10, 15, 20, 33, 50, 32, 49, 18, 30, 54, 23, 20, 54, 43, 23, 1, 3, 8, 83, 58, 58, 39)
```

We collected `{r} length(measurements)` measurements.

The average was `{r} mean(measurements)`.

And the total sum was `{r} sum(measurements)`.

Inline code - do some calculation and present in the text

Running code inside a Quarto file

script.R

```{r}
# Air particle measurements in a vector
measurements <- c(10, 15, 20, 33, 50, 32, 49, 18, 30, 54, 23, 20, 54, 43, 23, 1, 3, 8, 83, 58, 58, 39)
```

We collected `{r} length(measurements)` measurements.

The average was `{r} mean(measurements)`.

And the total sum was `{r} sum(measurements)`.

We collected 22 measurements.

The average was 32.9090909.

And the total sum was 724.

Inline code - do some calculation and present in the text

3. Version control - Git

Version control - Git

Version control is not track changes

Version control - Git

Since a Quarto file is plain text we can track all changes with version control

Conclusion

• Webpages
• Reports
• Presentations (like this one)
• Articles
• Your kappa?!