quarto.qmd

---
title: "Quarto"
author: "Uros Godnov"
subtitle: "How to report and reproduce your findings"
format:
  revealjs:
    theme: simple 
    slide-number: true
    embed-resources: true
    preview-links: auto
    footer: <https://quarto.org>
    transition: slide
    background-transition: fade
---

## Quarto - introduction {.smaller}

-   Released in June 2022.
-   Open-source scientific and technical publishing system.
-   Facilitates the creation of dynamic, reproducible documents, presentations, and reports.
-   Aims to produce high-quality, publication-ready outputs.
-   Supports multiple programming languages including R, Python, and Julia.
-   Enhances the reproducibility of scientific research.
-   Allows embedding of source code in documents for transparency.

## Historical development {.smaller}

-   Evolution of Computational Document Authoring:

    -   Before Quarto, R Markdown was a popular tool in the data science community for creating dynamic, reproducible documents using R. Increasing Demand for Multi-Language Support:

    -   As the data science field grew, there was a rising demand for tools that could support multiple programming languages (e.g., Python, Julia) alongside R. Integration with Jupyter Ecosystem:

-   Jupyter Notebooks gained popularity for interactive computing, creating a need for tools that could bridge R Markdown and Jupyter. Quarto's Development:

-   Quarto was developed to meet these evolving needs, offering a more flexible and powerful platform. It extended the capabilities of R Markdown by integrating with the Jupyter ecosystem and supporting multiple languages.

## Benefits {.smaller}

-   Enhanced Reproducibility in Scientific Research:

    -   Facilitates the creation of documents where data, code, and narrative are closely intertwined.

    -   Improves the transparency and verifiability of research findings.

-   Easy Collaboration Features:

    -   Supports collaborative workflows, making it simpler for teams to work together on documents.

    -   Version control friendly, integrates well with platforms like GitHub.

-   High-Quality Publishing Outputs:

    -   Capable of generating documents in various formats including HTML, PDF, and Word.

    -   Ensures professional-grade layout and typesetting for publication-ready outputs.

## Components

-   YAML header
-   code chunks
-   text

## YAML header - 1 {.smaller}

-   **Location and Structure**:

    -   At the top of the document, enclosed between **`---`** lines.

    -   Written in key-value pairs using YAML syntax.

-   **Document Metadata**:

    -   Title, author, and date.

    -   Additional info like keywords and abstract.

-   **Format Specifications**:

    -   Determines output format (HTML, PDF, Word).

    -   Customization options for each format.

-   **Code Chunk Options**:

    -   Global settings for all code blocks.

    -   Controls echo, warning, message, and error displays.



## YAML header - 2 {.smaller}

-   **Table of Contents and Navigation**:

    -   Configuration of depth, appearance, and placement.

    -   Section numbering enable/disable option.

-   **Citations and Bibliography**:

    -   Settings for citation processing.

    -   Bibliography file specification and style guide selection.

-   **Language Settings**:

    -   Controls for multilingual document support.

-   **Cross-Referencing and Linking**:

    -   Configuration for figure and table referencing.

    -   Hyperlinking and URL management settings.

## YAML - 3

::: columns
::: {.column width="50%"}
![](images/titleAndAuthor.png){width="485"}

![](images/styling.png){width="481"}
:::

::: {.column width="50%"}
![](images/execution.png){width="481"}
:::
:::



## Demo

- create a new quarto document

- replace the current YAML with this one:

```r
---
title: "Learning Quarto"
date: "2024-01-01"
subtitle: "The power of Quarto"
author: "Jane Doe"
abstract: "Quarto is a powerful tool for data science. We love Quarto!"
format: 
    html:
      toc: true
      toc_float: true
      toc-location: left
      mainfont: cursive
      embed-resources: true
---
```
- save and render document


## Demo

- add new header ***Loading packages** in the begining
- create new code chunk:

```r
library(tidyverse)
library(knitr)
library(gt)
```
- render the document. Observe.


## Executable Code {.smaller}

```r
#| echo: true
#| fig-width: 10
#| fig-height: 4.5
library(ggplot2)
ggplot(mtcars, aes(hp, mpg, color = am)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method = "loess")
```

```{r}
#| echo: false
#| fig-width: 10
#| fig-height: 4.5
library(ggplot2)
ggplot(mtcars, aes(hp, mpg, color = am)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method = "loess")
```

::: footer
Learn more: [Executable Code](https://quarto.org/docs/presentations/revealjs/#executable-code)
:::


## Demo {.smaller}

- in the existing quarto create a new code chunk
- copy the following code:

```r
#| echo: true
#| fig-width: 10
#| fig-height: 4.5
library(ggplot2)
ggplot(mtcars, aes(hp, mpg, color = am)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method = "loess")
```
- render the document. What can you observe?
- change the echo to false and render again. 
- in YAML header add:

```r
execution:
    echo: false
```
- render and observe. What changed?

## Update snippets

- go to [Snippet](https://posit.co/blog/6-productivity-hacks-for-quarto/)
- copy snippets to RStudio > Tools > Edit Code Snippets
- use Shift + Tab to autocomplete

![](images/clipboard-703634262.png)

## Column Layout - 1 {.smaller}

Arrange content into columns of varying widths:

```r
::: columns
::: {.column width="35%"}
#### Motor Trend Car Road Tests

The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles.
:::

::: {.column width="3%"}
:::

::: {.column width="62%"}
```{r}
knitr::kable(head(mtcars)[,c("mpg",	"cyl", "disp", "hp", "wt")])
```
:::
:::
```

## Column Layout - 2 {.smaller}


::: columns
::: {.column width="35%"}
#### Motor Trend Car Road Tests

The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles.
:::

::: {.column width="3%"}
:::

::: {.column width="62%"}
```{r}
knitr::kable(head(mtcars)[,c("mpg",	"cyl", "disp", "hp", "wt")])
```
:::

:::

::: footer
Learn more: [Multiple Columns](https://quarto.org/docs/presentations/revealjs/#multiple-columns)
:::


## Demo {.smaller}


- to existing Quarto document add new header ***Columns***
- create 2 columns, with 50 % and 50 % width
- in the first column add a code chunk:
```r
airquality %>% 
   head() %>% 
   kable()
```
- in the second column add a code chunk:
```r
airquality %>% 
   head() %>% 
   gt()
```
- render and observe

## Important

- displaying tables can be tricky
- ***never*** just list a name of a dataframe
- if dataframe is huge, rendering will take forever
- always go with the packages that are meant to display tables
- control the number of rows

## Cross-referencing a table

- label has to start with "tbl-"
```r
#| label: tbl-airquality
#| tbl-cap: "The airquality in New York in 1973"

airquality %>% 
   head() %>% 
   gt()

```
- in a code you have to reference a table with "@" prefix:

```r
In the table @tbl-airquality we collected data for 5 months.
```
## Demo

- create a new header called ***Cross referencing a table***.
- copy the code from previous slide and the text under new header
- render and observe

## Cross-referencing a picture (plot) 

- label has to start with "fig-"
- bug in quarto, it doesnt display title nor referencing part

```r
#| label: fig-airquality
#| fig-cap: "Ozone vs. temp"

airquality %>% 
   dplyr::select(Ozone, Temp) %>% 
   ggplot(., aes(x=Temp, y=Ozone))+
   geom_point()

The chart @fig-airquality shows the relationship between Ozone and Temp.

```


## Cross-referencing a inserted picture

- name must begin with "#fig-" prefix

```r
![kitten](mini/images/kitten-300-200.jpeg){#fig-kitten}


The kitten in the @fig-kitten is hungry.
```

## Demo

- in the current Quarto add header ***Cross referencing a figure***.
- find a picture online and cross-reference it
- render and observe



## Tabsets - 1 {.smaller .scrollable transition="slide"}

```r
::: panel-tabset
### Plot

```{r}
library(ggplot2)
ggplot(mtcars, aes(hp, mpg, color = am)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method = "loess")
```

### Data

```{r}
knitr::kable(mtcars)
```
:::
```

## Tabsets - 2

::: panel-tabset

### Plot 

```{r}
library(ggplot2)
ggplot(mtcars, aes(hp, mpg, color = am)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method = "loess")
```

### Data {.smaller}

```{r}
knitr::kable(mtcars)
```
:::

::: footer
Learn more: [Tabsets](https://quarto.org/docs/presentations/revealjs/#tabsets)
:::


## Demo

- add mtcars header to quarto document
- create tabset panel with 3 tabsets
- name them *dummy1*, mtcars, *dummy2*
- create a chunk for the second tabset and add:

```r
   mtcars %>% 
        head() %>% 
        gt()
```
## Callout bloks - 1

```r
::: {.callout-note}
Note that there are five types of callouts, including:
`note`, `warning`, `important`, `tip`, and `caution`.
:::

::: {.callout-tip}
## Tip with Title

This is an example of a callout with a title.
:::

::: {.callout-warning}
## Standardization

This is an example of a warning.
:::
```

## Callout bloks - 2

::: {.callout-note}
Note that there are five types of callouts, including:
`note`, `warning`, `important`, `tip`, and `caution`.
:::

::: {.callout-tip}
## Tip with Title

This is an example of a callout with a title.
:::

::: {.callout-warning}
## Standardization

This is an example of a warning.
:::

## Demo

- add new ***Callout warning*** after loading packages. State the document is meant only for learning purposes.

## Interactive Slides {.smaller transition="slide"}

Include Jupyter widgets and htmlwidgets in your presentations

```{r}
#| echo: false
#| fig-height: 5
library(leaflet)
leaflet() %>%
  addTiles() %>%  # Add default OpenStreetMap map tiles
  addMarkers(lat=49.4631, lng=1.0638, popup="NEOMA")
```


## Cache

- large chunks --> use cache
```r
#| cache: true

Sys.sleep(5)
```

- add new header ***Cache***.
- copy above code to the new chunk
- render, observe
- render again and observe