Quarto & Plotting

]

# Week 3: .fancy[Quarto & Plotting]

### <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:white;overflow:visible;position:relative;"><path d="M243.4 2.6l-224 96c-14 6-21.8 21-18.7 35.8S16.8 160 32 160v8c0 13.3 10.7 24 24 24H456c13.3 0 24-10.7 24-24v-8c15.2 0 28.3-10.7 31.3-25.6s-4.8-29.9-18.7-35.8l-224-96c-8-3.4-17.2-3.4-25.2 0zM128 224H64V420.3c-.6 .3-1.2 .7-1.8 1.1l-48 32c-11.7 7.8-17 22.4-12.9 35.9S17.9 512 32 512H480c14.1 0 26.5-9.2 30.6-22.7s-1.1-28.1-12.9-35.9l-48-32c-.6-.4-1.2-.7-1.8-1.1V224H384V416H344V224H280V416H232V224H168V416H128V224zM256 64a32 32 0 1 1 0 64 32 32 0 1 1 0-64z"/></svg> EMSE 6035: Marketing Analytics for Design Decisions
### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:white;overflow:visible;position:relative;"><path d="M304 128a80 80 0 1 0 -160 0 80 80 0 1 0 160 0zM96 128a128 128 0 1 1 256 0A128 128 0 1 1 96 128zM49.3 464H398.7c-8.9-63.3-63.3-112-129-112H178.3c-65.7 0-120.1 48.7-129 112zM0 482.3C0 383.8 79.8 304 178.3 304h91.4C368.2 304 448 383.8 448 482.3c0 16.4-13.3 29.7-29.7 29.7H29.7C13.3 512 0 498.7 0 482.3z"/></svg> John Paul Helveston
### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:white;overflow:visible;position:relative;"><path d="M152 24c0-13.3-10.7-24-24-24s-24 10.7-24 24V64H64C28.7 64 0 92.7 0 128v16 48V448c0 35.3 28.7 64 64 64H384c35.3 0 64-28.7 64-64V192 144 128c0-35.3-28.7-64-64-64H344V24c0-13.3-10.7-24-24-24s-24 10.7-24 24V64H152V24zM48 192H400V448c0 8.8-7.2 16-16 16H64c-8.8 0-16-7.2-16-16V192z"/></svg> September 11, 2024

]

---

# Quiz 1

### Download the template from the #class channel

### Make sure you unzip it!

### When done, submit your `quiz1.qmd` on Blackboard

]

]

---

# Week 3: .fancy[Quarto & Plotting]

### 1. Intro to Quarto
### 2. Intro to ggplot2

### Break

### 3. Project attributes & levels

---

# Week 3: .fancy[Quarto & Plotting]

### 1. .orange[Intro to Quarto]
### 2. Intro to ggplot2

### Break

### 3. Project attributes & levels

---

# "Literate programming"

> ### Treat programs as a "literature" understandable to **human beings**

]]

[Donald E. Knuth](https://en.wikipedia.org/wiki/Donald_Knuth)

]]

---

# .center[Quick demo]

<br>

# 1. Open `quarto_demo.qmd`

# 2. Click "Render"

---

# .center[Anatomy of a .qmd file]

<br>

# .red[Header]

# Markdown text

# R code

---

# Define overall document options in header

Basic html page

```
---
title: Your title
author: Author name
format: html
---
```

]

Add table of contents, change theme

```
---
title: Your title
author: Author name
toc: true
format:
  html:
    theme: united
---
```

More on themes at https://quarto.org/docs/output-formats/html-themes.html

]

---

# Render to multiple outputs

### PDF uses LaTeX

```
---
title: Your title
author: Author name
format: pdf
---
```

If you don't have LaTeX on your computer, install tinytex in R:

``` r
tinytex::install_tinytex()
```

]

### Microsoft Word

```
---
title: Your title
author: Author name
format: docx
---
```

]

---

# .center[Anatomy of a .qmd file]

<br>

# ~~Header~~

# .red[Markdown text]

# R code

---

# Right now, bookmark this! 👇

# https://commonmark.org/help/

# (When you have 10 minutes, do this! 👇)

# https://commonmark.org/help/tutorial/

---

# .center[Headers]

```markdown
# HEADER 1

## HEADER 2

### HEADER 3

#### HEADER 4

##### HEADER 5

###### HEADER 6
```

]

# HEADER 1

## HEADER 2

### HEADER 3

#### HEADER 4

##### HEADER 5

###### HEADER 6

]

---

# .center[Basic Text Formatting]

## Type this...

- `normal text`
- `_italic text_`
- `*italic text*`
- `**bold text**`
- `***bold italic text***`
- `~~strikethrough~~`
- `` `code text` ``

]

## ..to get this

- normal text
- _italic text_
- *italic text*
- **bold text**
- ***bold italic text***
- ~~strikethrough~~
- `code text`

]

---

# .center[Lists]

Bullet list:

``` r
- first item
- second item
- third item
```

- first item
- second item
- third item

]

Numbered list:

``` r
1. first item
2. second item
3. third item
```

1. first item
2. second item
3. third item

]

---

# .center[Links]

Simple **url link** to another site:

``` r
[Download R](http://www.r-project.org/)
```

[Download R](http://www.r-project.org/)

---

# Don't want to use Markdown?

# .red[Use Visual Mode!]

---

# .center[Anatomy of a .qmd file]

<br>

# ~~Header (think of this as the "settings")~~

# ~~Markdown text~~

# .red[R code]

---

# R Code

## Inline code

``` r
`r insert code here`
```

]]

## Code chunks

````markdown
```{r}
insert code here
insert more code here
```
````

]]

---

# Inline R code

``` r
The sum of 3 and 4 is `r 3 + 4`
```

Produces this:

The sum of 3 and 4 is 7

---

# R Code chunks

This code chunk...

````markdown
```{r}
library(palmerpenguins)

head(penguins)
```
````

]

...will produce this when compiled:

``` r
library(palmerpenguins)

head(penguins)
```

```
#> # A tibble: 6 × 8
#>   species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex     year
#>   <fct>   <fct>              <dbl>         <dbl>             <int>       <int> <fct>  <int>
#> 1 Adelie  Torgersen           39.1          18.7               181        3750 male    2007
#> 2 Adelie  Torgersen           39.5          17.4               186        3800 female  2007
#> 3 Adelie  Torgersen           40.3          18                 195        3250 female  2007
#> 4 Adelie  Torgersen           NA            NA                  NA          NA <NA>    2007
#> 5 Adelie  Torgersen           36.7          19.3               193        3450 female  2007
#> 6 Adelie  Torgersen           39.3          20.6               190        3650 male    2007
```

]

---

# Chunk options

Control what chunks output using options

All options [here](https://quarto.org/docs/reference/cells/cells-knitr.html)

---

# .center[Chunk output options]

````markdown
```{r}
#| echo: false

cat('hello world!')
```
````

Prints only **output**<br>(doesn't show code)

```
#> hello world!
```

]

````markdown
```{r}
#| eval: false

cat('hello world!')
```
````

Prints only **code**<br>(doesn't run the code)

``` r
cat('hello world!')
```

]

````markdown
```{r}
#| include: false

cat('hello world!')
```
````

Runs, but doesn't print anything

]

---

# message / warning

![](https://www.tidyverse.org/images/tidyverse_1.2.0/tidyverse_1-2-0_pkg_load.gif)

---

# message / warning

Drop messages and warnings in chunk settings

````markdown
```{r}
#| message: false
#| warning: false

library(tidyverse)
```
````

]

---

# A global `setup` chunk 🌍

````markdown
```{r}
#| label: setup
#| include: false

knitr::opts_chunk$set(
    warning = FALSE,
    message = FALSE,
    fig.path = "figs/",
    fig.width = 7.252,
    fig.height = 4,
    comment = "#>",
    fig.retina = 3
)
```
````

]

- Typically the first chunk
- All following chunks will use these options (i.e., sets global chunk options)
- You can (and should) use individual chunk options too
- Often where I load libraries, etc.

]

---

# Your turn

1) Open the `bears.qmd` file, and title it _"Bears Analysis"_

2) Create a "setup" code chunk to read in the `bear_killings.csv` data file<br>(HINT: You might want to look back at the `quarto_demo.qmd` file!).

3) Use text and code to find answers each of the following questions - show your code and results to justify each answer:

- Which months have the highest frequency of bear killings?
- Who has been killed more often by bears: hunters or hikers?
- How do the the number of bear attacks on men vs women compare?

HINT: Use `bears %>% count(variable)` to count how many rows are in the data for each unique value of `variable`

]

---

# Week 3: .fancy[Quarto & Plotting]

### 1. Intro to Quarto
### 2. .orange[Intro to ggplot2]

### Break

### 3. Project attributes & levels

---

]

# "Grammar of Graphics"

Concept developed by Leland Wilkinson (1999)

**ggplot2** package developed by Hadley Wickham (2005)

]

---

# Making plot layers with ggplot2

<br>

### 1. The data 
### 2. The aesthetic mapping (what goes on the axes?)
### 3. The geometries (points? bars? etc.)
### 4. The annotations / labels
### 5. The theme

---

# Layer 1: The data

``` r
head(mpg)
```

```
#> # A tibble: 6 × 11
#>   manufacturer model displ  year   cyl trans      drv     cty   hwy fl    class  
#>   <chr>        <chr> <dbl> <int> <int> <chr>      <chr> <int> <int> <chr> <chr>  
#> 1 audi         a4      1.8  1999     4 auto(l5)   f        18    29 p     compact
#> 2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compact
#> 3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compact
#> 4 audi         a4      2    2008     4 auto(av)   f        21    30 p     compact
#> 5 audi         a4      2.8  1999     6 auto(l5)   f        16    26 p     compact
#> 6 audi         a4      2.8  1999     6 manual(m5) f        18    26 p     compact
```

---

# Layer 1: The data

The `ggplot()` function initializes the plot with whatever data you're using

``` r
mpg %>% 
  ggplot()
```

]

]]

---

# Layer 2: The aesthetic mapping

The `aes()` function determines which variables will be _mapped_ to the geometries<br>(e.g. the axes)

``` r
mpg %>% 
* ggplot(aes(x = displ, y = hwy))
```

]

]]

---

# Layer 3: The geometries

Use `+` to add geometries, e.g. `geom_points()` for points

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
* geom_point()
```

]

]]

---

# Layer 4: The annotations / labels

Use `labs()` to modify most labels

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* labs(
*   x = "Engine displacement (liters)",
*   y = "Highway fuel economy (mpg)",
*   title = "Most larger engine vehicles are less fuel efficient"
* )
```

]

]

---

# Layer 5: The theme

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
  labs(
    x = "Engine displacement (liters)",  
    y = "Highway fuel economy (mpg)", 
    title = "Most larger engine vehicles are less fuel efficient"
  ) + 
* theme_bw()
```

]

]

---

### Common themes

`theme_bw()`

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* theme_bw()
```

]

`theme_minimal()`

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* theme_minimal()
```

]

---

### Common themes

`theme_classic()`

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* theme_classic()
```

]

`theme_void()`

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* theme_void()
```

]

---

### Other themes: [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes)

``` r
remotes::install_github("hrbrmstr/hrbrthemes")
```

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* hrbrthemes::theme_ipsum()
```

]

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* hrbrthemes::theme_ft_rc()
```

]

---

### Other themes: [ggthemes](https://jrnold.github.io/ggthemes/)

``` r
install.packages('ggthemes', dependencies = TRUE)
```

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* ggthemes::theme_economist()
```

]

``` r
mpg %>% 
  ggplot(aes(x = displ, y = hwy)) +
  geom_point() +
* ggthemes::theme_economist_white()
```

]

---

# More practice

# Open `ggplot2.qmd`

---

]

## Your turn

Open `practice.qmd`

Use the `mpg` data frame and ggplot to create these charts

]

---

# Extra practice

]

]

---

# Week 3: .fancy[Quarto & Plotting]

### 1. Intro to Quarto
### 2. Intro to ggplot2

### Break

### 3. .orange[Project attributes & levels]

---

# Model Relationships Table ([example](https://docs.google.com/spreadsheets/d/1Hmxfav_l1bubnaPkIiiMW0tZrFA-xblP9_ndN_6TB1I/edit?usp=sharing))

]

## Start defining attribute _levels_

---

# Defining attribute levels

## Continuous

- **Price**: 1, 2, 3, 4, 5 ($)
- **Power Output**: 60, 80, 120 (Watts)

## Discrete

- **Color**: Red, Blue, Yellow
- **Material**: Plastic, Aluminum, Glass

]

- Look at competitors
- Search web for values that cover the full set of values available today (and maybe some into the future)

]