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index.qmd
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---
format:
revealjs:
theme: [default, custom.css, styles.scss]
filters:
- reveal-auto-agenda
- lightbox
auto-agenda:
bullets: numbered
heading: Agenda
transition: fade
background-transition: fade
highlight-style: pygments
---
## {.title}
::: r-fit-text
Intro to [Quarto]{.flow}
:::
::: {style="font-size: 80px"}
Tracy Teal
:::
From Isabella Velásquez's R-Ladies St. Louis presentation
::: notes
Hi everybody! Thank you so much for joining today's session. I am so excited to introduce Quarto and many thanks to Laura and the R-Ladies St. Louis co-organizers for having me today hi there.
:::
# Introduction {.r-stretch}
## Instructions {.small}
::: incremental
- Slides: <https://tracykteal.quarto.pub/intro-to-quarto/>
- Session repo with instructions: <https://github.com/tracykteal/2022-10-27_intro-to-quarto>
- Exercise repo: <https://github.com/ivelasq/intro-to-quarto-exercises>
- rstudio.cloud Project: <https://rstudio.cloud/content/4823293>
:::
. . .
::: callout-tip
## Workshop Prep
To follow along with the exercises, please be sure that you:
- Are on the latest version of RStudio v2022.07 or later and have cloned the exercise repo
- Or, have a rstudio.cloud account and can access the project
- And, have a <https://quartopub.com/> account.
:::
::: notes
You have a few options of how to attend this session. On the README file of the GitHub repo for this session is a list of instructions and a link to the exercise repo. One option is that you have a local copy of the exercises already, and when we get to the different sections you can follow along with what I am doing on your own RStudio. Another option is that you sign up for RStudio Cloud and go into the project to follow along. It is also linked in the instructions. One benefit of this is that you don't have to have RStudio installed on your computer and the project is ready, the packages are installed for you, and you can save a copy of your work if you would like. But, please feel free to just watch the session and try things out on your own afterwards. The slides, repositories, and project will stay up so that you can try things out on your own time. One other thing to note is that Quarto has a lot of options for creating content, so I added some reference materials in the exercise repo README so that you can play around with other options other than the ones I show you.
:::
# About [Quarto]{.flow} {.r-stretch}
## What is Quarto®? {auto-animate="true"}
<center>
Quarto® is an
::: {.fragment .grow .semi-fade-out}
open-source
:::
::: {.fragment .grow .semi-fade-out}
scientific and technical
:::
::: {.fragment .grow .semi-fade-out}
publishing system
:::
::: {.fragment .grow .semi-fade-out}
built on Pandoc.
:::
</center>
::: notes
Quarto is an open-source scientific and technical publishing system built on Pandoc. Let's break this down: Open-source: RStudio believes that it's better for everyone if the tools used for research and science are free and open. Free software means more reproducibility, widespread sharing of knowledge and techniques, and elimination of cost barriers. You can also see the source code and contribute, too. Scientific and technical: Scientific and technical means that Quarto has specific things for journal articles or scientific papers, like support for code execution, citations, footnotes, scientific markdown, equations, citations, crossrefs, so many things. We'll be showing some of these later on, but Quarto definitely has the scientific publishing audience in mind. Publishing system: Quarto is a tool for writing dynamic documents that combine code, output, and text. It can embed output from Python, R, Julia, and Observable. Quarto can be rendered to create high-quality articles, reports, presentations, websites, blogs, and books in HTML, PDF, MS Word, ePub, and more formats. Pandoc is the tool working behind the scenes to change Quarto documents to their finalized format.Quarto documents are authored with markdown, which is a plain text format. But Pandoc markdown is very rich and lets you control your document in very specific ways while being easy to read and write. We'll cover this as well.
:::
## Quarto Origins
::: incremental
- Open source project sponsored by Posit Software, PBC (formerly RStudio)
- We've had 10 years of experience with R Markdown
- But there are a lot of other programming languages...
:::
. . .
Can we reimplement R Markdown such that it's not tied to R?
::: aside
Check out [JJ Allaire's R Medicine Keynote](https://www.youtube.com/watch?v=9jGc0TxoRco)!
:::
::: notes
R Markdown is a file format for making dynamic documents with R. However, you need to call it from R to use it, and it was depedentn on knitr. If you're a Python user, it means you need to install R to use R Markdown. Quarto is a tool that you can call from the terminal or command line, and is independent from the computational systems. Quarto supports knitr, and can support others. So, you can think of Quarto as the next generation R Markdown that is fundamentally multilanguage and multiengine.
:::
## Quarto Goals
::: incremental
- Create computational documents that hold source code for automation and reproducibility
- Reduce how difficult it is to make a scientific document
- Enable "single-source publishing" --- create Word, PDFs, HTML, etc. from one source
:::
::: aside
Check out [JJ Allaire's R Medicine Keynote](https://www.youtube.com/watch?v=9jGc0TxoRco)!
:::
::: notes
So the goals are to create these dynamic documents that can be reproducible and automated. \[story about building documents\]. For single-source publishing, you often need to create all sorts of output, like things that are printed, on the web, on the mobile. The idea is to being able to make publications from one source.
:::
## A new tool for literate programming
::: columns
::: {.column width="{50%\""}
::: {.fragment .fade-in}
:::
:::
::: {.column width="{50%\""}
::: {.fragment .fade-in}
{height="600px"}
:::
:::
:::
::: aside
Check out [JJ Allaire's R Medicine Keynote](https://www.youtube.com/watch?v=9jGc0TxoRco)!
:::
::: notes
Quarto sits inside the big and broad literate programming world, which mixes narrative in text form with code for formatted outputs like documents and webpages and more. \[click\] There are lots of literate programming systems that support computation, like R Markdown, Org Mode, Jupyter Book, and now there is Quarto!
:::
## Why a new system?
::: incremental
- At its core, Quarto is multilingual and independent of computational systems
- Has expanded upon R Markdown to add new languages and can add more in the future
:::
. . .
Let's bring R Markdown to everybody!
::: notes
So, if there already exist literate programming tools out there, why create a new one, especially since RStudio is also behind R Markdown? Like mentioned earlier, Quarto was built from the start to support multiple computational systems and ecosystems. This new system brings R Markdown to everybody.
:::
## Why is it called "Quarto"?
::: columns
::: {.column width="60%"}
::: {style="font-size:28px"}
"Quarto is the format of a book or<br>pamphlet produced from full sheets<br>printed with eight pages of text, four to a<br>side, then folded twice to produce four leaves."
--- Wikipedia
:::
:::
::: {.column width="40%"}
:::
:::
::: aside
Image based on one from gutenberg.org
:::
::: notes
According to the website, the developers wanted to use a name that had meaning in the history of publishing and ulitimately landed on Quarto. A quarto is an 8-page double-sided booklet, made by folding a single sheet of paper into four sections.
:::
## Quarto Formats
::: panel-tabset
### Websites
{height="400"}
### Books
{height="400"}
### Blogs
{height="400"}
### Presentations
{height="400"}
### Journals
{height="400"}
:::
::: notes
Quarto can make very flexible websites, or books which are a a Quarto website that can be rendered to Word, ePub, etc., blogs with listings and posts and RSS feeds, Quarto has deep feature set for presentations with reveal.js optimized for scientific content, and of course, publishing for journals. There is custom format systems and the ability to flexibly adapt LaTeX templates.
:::
## Quarto Engines
### knitr
::: notes
An engine is the tool that runs code. This is the underlying structure that creates documents from the source, the Quarto markdown file or the QMD file. When we render a Quarto document, first, the knitr engine executes all of the code chunks and generates an intermediary markdown file that includes both the code and code output. Then that markdown file is processed by pandoc to create the finished document. Since Quarto uses knitr, most Rmd files can be used unmodified.
:::
------------------------------------------------------------------------
## knitr {.small}
::: columns
::: {.column width="50%"}
---
title: "ggplot2 demo"
format:
html:
code-fold: true
---
## Meet Quarto
Quarto enables you to weave together content and executable code into a finished document. To learn more about Quarto see <https://quarto.org>.
```{{r}}
#| label: plot-penguins
#| echo: false
#| message: false
#| warning: false
library(tidyverse)
library(palmerpenguins)
ggplot(penguins,
aes(x = flipper_length_mm, y = bill_length_mm)) +
geom_point(aes(color = species, shape = species)) +
scale_color_manual(values = c("darkorange","purple","cyan4")) +
labs(
title = "Flipper and bill length",
subtitle = "Dimensions for penguins at Palmer Station LTER",
x = "Flipper length (mm)", y = "Bill length (mm)",
color = "Penguin species", shape = "Penguin species"
) +
theme_minimal()
```
:::
::: {.column width="50%"}
:::
:::
::: notes
This is a Quarto document with the extension .qmd (on the left) along with its rendered version as HTML (on the right). You could also choose to render it into other formats like PDF, MS Word, etc. This is the basic model for Quarto publishing---take a source document and render it to a variety of output formats.
:::
## Quarto Engines
### Jupyter
::: notes
The structure is similar for Jupyter, we just are running documents natively through the Jupyter engine. Like R Marukdown, you can render Jupyter notebooks with Quarto, too. Jupyter will support any other language that has a Jupyter kernal, and right now, there's a lot of Quarto functionality for Python and Julia through Jupyter. But, this is part of the multilingualism that we discussed earlier, where you can keep adding languages if you swap out different engines. This also means you can have a shared syntax and format across languages, since the backend is the same.
:::
------------------------------------------------------------------------
## Jupyter {.small}
::: columns
::: {.column width="50%"}
---
title: "Palmer Penguins Demo"
format:
html:
code-fold: true
jupyter: python3
---
## Meet Quarto
Quarto enables you to weave together content and executable code into a finished document. To learn more about Quarto see <https://quarto.org>.
```{{python}}
#| echo: false
#| message: false
import pandas as pd
import seaborn as sns
from palmerpenguins import load_penguins
sns.set_style('whitegrid')
penguins = load_penguins()
g = sns.lmplot(x="flipper_length_mm",
y="body_mass_g",
hue="species",
height=7,
data=penguins,
palette=['#FF8C00','#159090','#A034F0']);
g.set_xlabels('Flipper Length');
g.set_ylabels('Body Mass');
```
:::
::: {.column width="50%"}
:::
:::
## Why Quarto?
### A unified ecosystem
::: incremental
- R Markdown has a lot of packages doing lots of different things
- Quarto has a shared expression for core features
:::
::: notes
So this is all good and well, but you may be wondering should you switch to Quarto if you already have another tool that you really like, you may be wondering whether or not you should switch. Here are some considerations. Quarto has a shared expression for core features. If you used the packages from the R Markdown ecosystem, then you may have had to switch between different ways of doing the same thing. In Quarto, you have a shared core syntax that is the same across all formats. Things like tabset, code folding, cross references in the same way. Another example is that Quarto has a universal theming system based on SCSS for all HTML output where core variables defined by bslib and so it is compatible with Shiny, flexdashboard, and R Markdown themes. So, users can create very consistent and organized theming across content.
:::
## Why Quarto? {.scrollable}
### New features
- Cross references
- Advanced layout
- Figure/layout panels
- Callouts
- Diagrams
- Extensions
- Interactivity
- YAML intelligence
- Publishing
- Conditional content
- Notebook filters
::: notes
R Markdown isn't going away but big new features will be in Quarto, things like YAML intelligence, figure panels, layouts, which we'll cover later in the session.
:::
## Why Quarto? {.small}
### Lua-based extension system
::: panel-tabset
#### Shortcodes
{height="400"}
#### Journal
{height="400"}
#### Formats
{height="400"}
#### Revealjs
{height="400"}
:::
::: notes
Quarto also supports extensions. Quarto extensions are written in Lua, meaning that they are not language specific. So, you can use the same extension in a Jupyter file or a knitr file. Shortcodes let you add content, like fontawesome icons that you have seen in this presentation, or videos from YouTube. Filters let you add new markdown syntax for extended features. And formats are custom formats. There are built in extensions and then community built ones, if you search for Awesome Quarto, there are a list of them there.
:::
# How to use [Quarto]{.flow} {.r-stretch}
## Quarto Installation
::: aside
quarto.org
:::
::: notes
When you download the Quarto CLI, though, that's all you need to run Quarto, so you can use just your Terminal or Command Line Interface for everything that we'll explore, but you will need to install the engines if you're going to run code with the CLI.
:::
## Quarto Tooling
::: {layout-ncol="2" align="center"}
{width="160"}
{width="160"}
{width="160"}
{width="160"}
:::
``` {.bash filename="Terminal"}
quarto render
```
::: notes
Part of the multilingualism of Quarto is that you are not tied to one tool. Quarto is meant for collaboration either within data science teams or across data science teams. So if someone is familiar with Jupyter Lab, but someone else likes to work in RStudio, they can still work on the same Quarto documents without having to switch to one tool or the other.
For RStudio users, Quarto is bundled and preinstalled with v2022.07 and later. There are a lot of features that are built into RStudio for Quarto documents. We didn't want to limit Quarto enhancements to just RStudio. VS Code has an extension so you can YAML completion and linting and other features for writing Quarto documents, and you can preview documents in Jupyter Notebooks and Jupyter Labs.
:::
## Working in RStudio {.small}
### Rendering
Use the Render button ({width="25" height="20"}) in the RStudio IDE to render the file and preview the output with a single click or keyboard shortcut (<kbd>⇧</kbd><kbd>⌘</kbd><kbd>K</kbd>).
Automatically render on save by checking the Render on Save option:
::: notes
In RStudio, you can use the Render button to render the file, or take it through that process of convering to markdown, pandoc processing, etc. and preview the output with a single click. If you're familiar with R Markdown, it is where the knit button would show for those document. If you prefer to automatically render whenever you save, you can check the Render on Save option on the editor toolbar. The preview will update whenever you re-render the document. Side-by-side preview works for both HTML and PDF outputs.
:::
------------------------------------------------------------------------
## YAML Intelligence {.small}
YAML code completion is available for project files, YAML front matter, and executable cell options:
{width="400"}
If you have incorrect YAML it will also be highlighted when documents are saved:
{width="400"}
::: {style="color: #C04483"}
Let's try it!
:::
::: notes
Quarto has YAML intelligence in RStudio and VS code. YAML intelligence means completion and diagnostics for errors, and its' available for project files, YAML front matter, and executable cell options. This makes it easy to write YAML and see what has gone wrong rather than getting error messages that are really hard to decipher.
:::
## Working with the RStudio Visual Editor {.small}
. . .
::: {style="color: #C04483"}
Let's try it!
:::
::: notes
RStudio has two options for editing documents: visual (on the left) and source (on the right). RStudio's visual editor offers an WYSIWYM authoring experience for markdown. So formatting (e.g. bolding text) you can use the toolbar, a keyboard shortcut (⌘B), or the markdown construct (**bold**). The plain text source code underlying the document is written for you and you can view/edit it at any point by switching to source mode for editing. You can toggle back and forth these two modes by clicking on Source and Visual in the editor toolbar (or using the keyboard shortcut ⌘⇧ F4).
:::
## Contents of a Quarto Document
::: {layout-ncol="3"}
:::
::: notes
A Quarto document contains three types of content: a YAML header, code chunks, and markdown text.
:::
## YAML {.small}
::: {layout-ncol="2"}
- "Yet another markup language"
- Metadata of your document
- Demarcated by three dashes (`---`) on either end
- Uses key-value pairs in the format `key: value`
:::
::: notes
Quarto documents usually start with an (optional) YAML header demarcated by three dashes on either end. The basic syntax of YAML uses key-value pairs in the format key: value. It controls the output of the document and contain metadata for your document, like title and author.
:::
## YAML {.small auto-animate="true"}
``` yaml
---
title: "Penguins, meet Quarto!"
format: html
editor: visual
---
```
::: notes
Other YAML fields commonly found in headers of documents include metadata like author, subtitle, date as well as customization options like theme, fontcolor, fig-width, etc.
:::
## YAML {.small auto-animate="true"}
``` yaml
---
title: "Penguins, meet Quarto!"
subtitle: "Intro to Quarto Exercise"
format: html
editor: visual
---
```
. . .
::: {style="color: #9054FF"}
Let's try it!
:::
[All YAML fields for HTML documents](https://quarto.org/docs/reference/formats/html.html){preview-link="true"}
## Code Chunks {.small}
::: {layout-ncol="2"}
- Code chunks begin and end with three backticks (usually)
- Code chunks are identified with a programming language in between `{}`
- Can include optional chunk options, in YAML style, identified by `#|` at the beginning of the line
:::
::: notes
Code chunks are identified with three backticks, the language in curly brackets, and can have optional chunk options identified by the hashpipe at the beginning of the line within the chunk.
:::
## Code Chunks {.small auto-animate="true"}
```` markdown
```{{r, label="plot-penguins", warning=FALSE, echo=FALSE}}
ggplot(penguins,
aes(x = flipper_length_mm, y = bill_length_mm)) +
geom_point(aes(color = species, shape = species)) +
scale_color_manual(values = c("darkorange","purple","cyan4")) +
labs(
title = "Flipper and bill length",
subtitle = "Dimensions for penguins at Palmer Station LTER",
x = "Flipper length (mm)", y = "Bill length (mm)",
color = "Penguin species", shape = "Penguin species"
) +
theme_minimal()
```
````
## Code Chunks {.small auto-animate="true"}
```` markdown
```{{r}}
#| label: plot-penguins
#| warning: false
#| echo: false
ggplot(penguins,
aes(x = flipper_length_mm, y = bill_length_mm)) +
geom_point(aes(color = species, shape = species)) +
scale_color_manual(values = c("darkorange","purple","cyan4")) +
labs(
title = "Flipper and bill length",
subtitle = "Dimensions for penguins at Palmer Station LTER",
x = "Flipper length (mm)", y = "Bill length (mm)",
color = "Penguin species", shape = "Penguin species"
) +
theme_minimal()
```
````
## Code Chunks {.small auto-animate="true"}
```` markdown
```{{r}}
#| label: plot-penguins
#| warning: false
#| echo: false
#| fig.alt: "Scatterplot with flipper length in millimeters on
#| the x-axis, bill length in millimeters on the y-axis, colored
#| by species, showing a slightly positive relationship with
#| Chinstrap penguins having higher bill length but lower body
#| mass, Adelie with low bill length and low body mass, and
#| Gentoo with high body mass and high bill length."
ggplot(penguins,
aes(x = flipper_length_mm, y = bill_length_mm)) +
geom_point(aes(color = species, shape = species)) +
scale_color_manual(values = c("darkorange","purple","cyan4")) +
labs(
title = "Flipper and bill length",
subtitle = "Dimensions for penguins at Palmer Station LTER",
x = "Flipper length (mm)", y = "Bill length (mm)",
color = "Penguin species", shape = "Penguin species"
) +
theme_minimal()
```
````
::: notes
The new hashpipe allows for consistency across Jupyter and knitr.
:::
## Code Chunks {.small}
::: {style="color: #039FA5"}
Let's try it!
:::
::: notes
In addition to rendering the complete document to view the results of code chunks you can also run each code chunk interactively in the RStudio editor by clicking the icon or keyboard shortcut (⇧⌘⏎). RStudio executes the code and displays the results either inline within your file or in the Console, depending on your preference.
:::
## Code Chunks {.small}
### Cross referencing
```` markdown
```{{r}}
#| label: fig-penguins
#| warning: false
ggplot(penguins,
aes(x = flipper_length_mm, y = bill_length_mm)) +
geom_point(aes(color = species, shape = species)) +
scale_color_manual(values = c("darkorange", "purple", "cyan4")) +
labs(
title = "Flipper and bill length",
subtitle = "Dimensions for penguins at Palmer Station LTER",
x = "Flipper length (mm)",
y = "Bill length (mm)",
color = "Penguin species",
shape = "Penguin species"
) +
theme_minimal()
```
````
```
See @fig-penguins.
```
## Code Chunks
### Cross referencing
{fig-align="center"}
## Multiple Figures
Put two plots side by side:
```{{r}}
#| layout-ncol: 2
#| warning: false
ggplot(penguins,
aes(x = flipper_length_mm, y = bill_length_mm)) +
geom_point(aes(color = species, shape = species))
ggplot(data = penguins, aes(x = flipper_length_mm)) +
geom_histogram(aes(fill = species),
alpha = 0.5,
position = "identity")
```
::: notes
Let's add another plot to our chunk. Our goal is to display these plots side-by-side.
:::
## Multiple Figures
Put two plots side by side:
## Multiple Figures
Put two plots side by side:
```{{r}}
#| layout: "[[30, 70]]"
#| warning: false
ggplot(penguins,
aes(x = flipper_length_mm, y = bill_length_mm)) +
geom_point(aes(color = species, shape = species))
ggplot(data = penguins, aes(x = flipper_length_mm)) +
geom_histogram(aes(fill = species),
alpha = 0.5,
position = "identity")
```
## Code Options for All Chunks {.small}
Use the YAML to control options for all code chunks.
Hide all of the code and just show the output by specifying `echo: false` within the `execute` option in the YAML.
### Echo
::: {layout-ncol="2"}
### One chunk
```{{r}}
#| label: plot-penguins
#| echo: false
ggplot(penguins,
aes(x = flipper_length_mm, y = bill_length_mm)) +
geom_point(aes(color = species, shape = species)) +
scale_color_manual(values = c("darkorange","purple","cyan4")) +
labs(
title = "Flipper and bill length",
subtitle = "Dimensions for penguins at Palmer Station LTER",
x = "Flipper length (mm)", y = "Bill length (mm)",
color = "Penguin species", shape = "Penguin species"
) +
theme_minimal()
```
### All chunks
``` {{yaml}}
---
title: "Hello, Quarto!"
format: html
editor: visual
execute:
echo: false
---
```
:::
## Code Options for All Chunks {.small}
### Code Folding
``` {{yaml}}
---
title: "Hello, Quarto!"
format:
html:
code-fold: true
---
```
### Code Tools
``` {{yaml}}
---
title: "Hello, Quarto!"
format:
html:
code-tools:
source: https://quarto.org
---
```
## Code Options for All Chunks {.small}
### Code Linking
**Needs downlit package**
:::{layout-ncol=2}
``` {{yaml}}
---
title: "Hello, Quarto!"
format:
html:
code-link: true
---
```
::::
::: notes
You might want to fold it and allow readers to view it at their discretion. You can do this via the code-fold option. Remove the echo option we previously added and add the code-fold HTML format option.
:::
## Markdown Text {.small}
::: {layout-ncol="2"}
- Markdown is a lightweight language for creating formatted text
- Quarto is based on Pandoc and uses its variation of markdown as its underlying document syntax
:::
::: notes
Markdown is a lightweight markup language for creating formatted text using a plain-text editor. Quarto uses markdown syntax for text.
:::
## Markdown Text {.small}
```{=html}
<div class="sourceCode">
<pre class="sourceCode markdown">
<code class="sourceCode markdown">
The `penguins` data from the [**palmerpenguins**](https://allisonhorst.github.io/palmerpenguins "palmerpenguins R package") package contains size measurements for `r nrow(penguins)` penguins from three species observed on three islands in the Palmer Archipelago, Antarctica.
</code>
</pre>
</div>
```
The `penguins` data from the [**palmerpenguins**](https://allisonhorst.github.io/palmerpenguins "palmerpenguins R package") package contains size measurements for 344 penguins from three species observed on three islands in the Palmer Archipelago, Antarctica.
::: notes
If using the visual editor, you won't need to learn much markdown syntax for authoring your document as you can use the menus and shortcuts to add a header, bold text, insert a table, etc. If using the source editor, you can achieve these with markdown expressions like ##, **bold**, etc.
:::
------------------------------------------------------------------------
### Markdown Text
### Formatting
+-----------------------------------+-------------------------------+
| Markdown Syntax | Output |
+===================================+===============================+
| *italics* and **bold** | *italics* and **bold** |
+-----------------------------------+-------------------------------+
| superscript^2^ / subscript~2~ | superscript^2^ / subscript~2~ |
+-----------------------------------+-------------------------------+
| ~~strikethrough~~ | ~~strikethrough~~ |
+-----------------------------------+-------------------------------+
| `verbatim code` | `verbatim code` |
+-----------------------------------+-------------------------------+
------------------------------------------------------------------------
### Markdown Text {.small .scrollable}
### Images and Links
+------------------------------------+---------------------------------+
| Markdown Syntax | Output |
+====================================+=================================+
| <https://quarto.org> | <https://quarto.org> |
+------------------------------------+---------------------------------+
| [Quarto](https://quarto.org) | [Quarto](https://quarto.org) |
+------------------------------------+---------------------------------+
|  |  |
+------------------------------------+---------------------------------+
::: aside
Photo by <a href="https://unsplash.com/@corneliusventures?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Cornelius Ventures</a> on <a href="https://unsplash.com/s/photos/penguin?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText">Unsplash</a>
:::
## Markdown Text {.small auto-animate="true"}
### Tables
``` {{markdown}}
| Right | Left | Default | Center |
|------:|:-----|---------|:------:|
| 12 | 12 | 12 | 12 |
| 123 | 123 | 123 | 123 |
| 1 | 1 | 1 | 1 |
```
| Right | Left | Default | Center |
|------:|:-----|---------|:------:|
| 12 | 12 | 12 | 12 |
| 123 | 123 | 123 | 123 |
| 1 | 1 | 1 | 1 |
## Markdown Text {.small auto-animate="true"}
### Tables
``` {{markdown}}
| Right | Left | Default | Center |
|------:|:-----|---------|:------:|
| 12 | 12 | 12 | 12 |
| 123 | 123 | 123 | 123 |
| 1 | 1 | 1 | 1 |
: Table Column Widths {tbl-colwidths="[10,30,30,30]"}
```
| Right | Left | Default | Center |
|------:|:-----|---------|:------:|
| 12 | 12 | 12 | 12 |
| 123 | 123 | 123 | 123 |
| 1 | 1 | 1 | 1 |
: Table Column Widths {tbl-colwidths="\[10,30,30,30\]"}
. . .
::: {style="color: #FF66C4"}
Let's try it!
:::
[Quarto guide for Markdown basics](https://quarto.org/docs/authoring/markdown-basics.html){preview-link="true"}
## Quarto Authoring {.small}
### Diagrams
Quarto has native support for embedding Mermaid and Graphviz diagrams.
```{mermaid}
%%| fig-width: 6
%%| echo: fenced
flowchart LR
A[1] --> B(2)
B --> C{3}
C --> D[4]
C --> E[5]
```
::: notes
There is also native support for diagrams, where the syntax is similar as R or Python where the execution is being run by Quarto. This is a Mermaid diagram, which is a newer project supported on GitHub where you can use it in their documents as well, so it's a pretty handy tool to get to know.
:::
## Quarto Authoring
### Equations
``` {{markdown}}
$$E = mc^{2}$$
```
$$E = mc^{2}$$
## Quarto Authoring {.small}
### Title Banners
::: {layout-ncol="2"}
HTML pages rendered with Quarto include a formatted title banner at the start of the article.
:::
## Title Banners {auto-animate="true"}
``` yaml
---
title: "Penguins, meet Quarto!"
format: html
editor: visual
---
```
. . .
Toggle on...
## Title Banners {auto-animate="true"}
``` yaml
---
title: "Penguins, meet Quarto!"
title-block-banner: true
format: html
editor: visual
---
```
## Title Banners {auto-animate="true"}
Use a color...
``` yaml
---