RMarkdown & Plotting

]

# Week 3: .fancy[RMarkdown & 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 2.587C251.4-.8625 260.6-.8625 268.6 2.587L492.6 98.59C506.6 104.6 514.4 119.6 511.3 134.4C508.3 149.3 495.2 159.1 479.1 160V168C479.1 181.3 469.3 192 455.1 192H55.1C42.74 192 31.1 181.3 31.1 168V160C16.81 159.1 3.708 149.3 .6528 134.4C-2.402 119.6 5.429 104.6 19.39 98.59L243.4 2.587zM256 128C273.7 128 288 113.7 288 96C288 78.33 273.7 64 256 64C238.3 64 224 78.33 224 96C224 113.7 238.3 128 256 128zM127.1 416H167.1V224H231.1V416H280V224H344V416H384V224H448V420.3C448.6 420.6 449.2 420.1 449.8 421.4L497.8 453.4C509.5 461.2 514.7 475.8 510.6 489.3C506.5 502.8 494.1 512 480 512H31.1C17.9 512 5.458 502.8 1.372 489.3C-2.715 475.8 2.515 461.2 14.25 453.4L62.25 421.4C62.82 420.1 63.41 420.6 63.1 420.3V224H127.1V416z"/></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="M224 256c70.7 0 128-57.31 128-128s-57.3-128-128-128C153.3 0 96 57.31 96 128S153.3 256 224 256zM274.7 304H173.3C77.61 304 0 381.6 0 477.3c0 19.14 15.52 34.67 34.66 34.67h378.7C432.5 512 448 496.5 448 477.3C448 381.6 370.4 304 274.7 304z"/></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="M96 32C96 14.33 110.3 0 128 0C145.7 0 160 14.33 160 32V64H288V32C288 14.33 302.3 0 320 0C337.7 0 352 14.33 352 32V64H400C426.5 64 448 85.49 448 112V160H0V112C0 85.49 21.49 64 48 64H96V32zM448 464C448 490.5 426.5 512 400 512H48C21.49 512 0 490.5 0 464V192H448V464z"/></svg> September 14, 2022

]

---

# Week 3: .fancy[RMarkdown & Plotting]

### 1. Intro to RMarkdown

### QUIZ 1

### 2. Intro to ggplot2
### 3. Project attributes & levels

---

# Week 3: .fancy[RMarkdown & Plotting]

### 1. .orange[Intro to RMarkdown]

### QUIZ 1

### 2. Intro to ggplot2
### 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)

]]

---

background-image: url(images/horst_monsters_rmarkdown.png)
background-size: contain
background-color: #FFFFFF

---

# .center[Anatomy of a .Rmd file]

<br>

# YAML (**Y**et **A**nother **M**arkdown **L**anguage)

# Markdown text

# R code

---

# Quick demo

# Open `rmd_demo.Rmd`, then click "knit"

---

# Define overall document options in YAML

Basic html page
```yaml
---
title: Your title here
author: Your name here
output: html_document
---
```

]

Add table of contents, change theme

```yaml
---
title: Your title here
author: Your name here
output:
  html_document:
    toc: true
    toc_float: true
    theme: flatly
---
```

Other themes at https://bootswatch.com/

]

---

# 🧶 Knit to multiple outputs

```r
rmarkdown::render("rmd_demo.Rmd", output_format = "all")
```

]

```yaml
---
title: Your title here
author: Your name here
output:
  html_document:
    toc: true
    toc_float: true
    theme: flatly
  word_document: default
  pdf_document: default
---
```

]

---

# .center[Anatomy of a .Rmd file]

<br>

# ~~YAML (**Y**et **A**nother **M**arkdown **L**anguage)~~

# .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/)

---

# Back to `rmd_demo.Rmd`

---

# .center[Anatomy of a .Rmd file]

<br>

# ~~YAML (**Y**et **A**nother **M**arkdown **L**anguage)~~

# ~~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}
bears %>%
  count(month)
```
````

]

...will produce this when compiled:

```r
bears %>%
  count(month)
```

```
#> # A tibble: 12 × 2
#>    month     n
#>    <dbl> <int>
#>  1     1     3
#>  2     2     1
#>  3     3     1
#>  4     4     4
#>  5     5    18
#>  6     6    20
#>  7     7    27
#>  8     8    28
#>  9     9    25
#> 10    10    25
#> 11    11    12
#> 12    12     2
```

]

---

# Chunk options

Control what chunks output using options inside `{r}`:

Example: `{r, echo=FALSE, message=FALSE}`

---

# .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 🌍

One chunk to rule them all!

````markdown
```{r setup, include = FALSE}
knitr::opts_chunk$set(
  warning = FALSE,
  message = FALSE,
  comment = "#>",
  fig.retina = 3,
  fig.path = "figs/"
)
```
````

]

- A special chunk label: `setup`
- Typically the first chunk
- All following chunks will use these options (i.e., sets global chunk options)
- **Tip**: set `include=FALSE`
- You can (and should) use individual chunk options too

]

---

# Your turn

1) Open the `bears.Rmd` 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 `rmd_demo.Rmd` 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`

]

---

# Quiz 1

### Link is in the #class channel

]

]

---

# Week 3: .fancy[RMarkdown & Plotting]

### 1. Intro to RMarkdown

### QUIZ 1

### 2. .orange[Intro to ggplot2]
### 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.Rmd`

---

]

# Your turn

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

]

---

# Extra practice

]

]

---

# Week 3: .fancy[RMarkdown & Plotting]

### 1. Intro to RMarkdown

### QUIZ 1

### 2. Intro to ggplot2
### 3. .orange[Project attributes & levels]

---

# Model Relationships Table ([example](https://docs.google.com/spreadsheets/d/1iwMI9cbJjB6J8wghZY6Y_fCOSt7MDsUTnSuuC58_xjU/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)

]