Session 7

class: center, middle, inverse, title-slide

.title[
# Session 7
]
.subtitle[
## More Rmarkdown
]

---

## Typography

Text can be **bold**, _italic_, ~~strikethrough~~, or `inline code`.

```markdown
 *italic*
 **bold**
 ~~strikethrough~~
 `inline code`
[link](https://example.com)
```
---
### Code Blocks

#### R Code

```r
ggplot(gapminder) +
  aes(x = gdpPercap, y = lifeExp, size = pop, color = country) +
  geom_point() +
  facet_wrap(~year)
```

---

## Tables

```r
knitr::kable(head(mtcars), format = 'html')
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;">   </th>
   <th style="text-align:right;"> mpg </th>
   <th style="text-align:right;"> cyl </th>
   <th style="text-align:right;"> disp </th>
   <th style="text-align:right;"> hp </th>
   <th style="text-align:right;"> drat </th>
   <th style="text-align:right;"> wt </th>
   <th style="text-align:right;"> qsec </th>
   <th style="text-align:right;"> vs </th>
   <th style="text-align:right;"> am </th>
   <th style="text-align:right;"> gear </th>
   <th style="text-align:right;"> carb </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Mazda RX4 </td>
   <td style="text-align:right;"> 21.0 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 160 </td>
   <td style="text-align:right;"> 110 </td>
   <td style="text-align:right;"> 3.90 </td>
   <td style="text-align:right;"> 2.620 </td>
   <td style="text-align:right;"> 16.46 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Mazda RX4 Wag </td>
   <td style="text-align:right;"> 21.0 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 160 </td>
   <td style="text-align:right;"> 110 </td>
   <td style="text-align:right;"> 3.90 </td>
   <td style="text-align:right;"> 2.875 </td>
   <td style="text-align:right;"> 17.02 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Datsun 710 </td>
   <td style="text-align:right;"> 22.8 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 108 </td>
   <td style="text-align:right;"> 93 </td>
   <td style="text-align:right;"> 3.85 </td>
   <td style="text-align:right;"> 2.320 </td>
   <td style="text-align:right;"> 18.61 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hornet 4 Drive </td>
   <td style="text-align:right;"> 21.4 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 258 </td>
   <td style="text-align:right;"> 110 </td>
   <td style="text-align:right;"> 3.08 </td>
   <td style="text-align:right;"> 3.215 </td>
   <td style="text-align:right;"> 19.44 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hornet Sportabout </td>
   <td style="text-align:right;"> 18.7 </td>
   <td style="text-align:right;"> 8 </td>
   <td style="text-align:right;"> 360 </td>
   <td style="text-align:right;"> 175 </td>
   <td style="text-align:right;"> 3.15 </td>
   <td style="text-align:right;"> 3.440 </td>
   <td style="text-align:right;"> 17.02 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 2 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Valiant </td>
   <td style="text-align:right;"> 18.1 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 225 </td>
   <td style="text-align:right;"> 105 </td>
   <td style="text-align:right;"> 2.76 </td>
   <td style="text-align:right;"> 3.460 </td>
   <td style="text-align:right;"> 20.22 </td>
   <td style="text-align:right;"> 1 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 1 </td>
  </tr>
</tbody>
</table>

---
exclude: false

```r
DT::datatable(head(mtcars), fillContainer = FALSE, options = list(pageLength = 4))
```

<div class="datatables html-widget html-fill-item-overflow-hidden html-fill-item" id="htmlwidget-550269c3280332081e64" style="width:100%;height:auto;"></div>
<script type="application/json" data-for="htmlwidget-550269c3280332081e64">{"x":{"filter":"none","vertical":false,"fillContainer":false,"data":[["Mazda RX4","Mazda RX4 Wag","Datsun 710","Hornet 4 Drive","Hornet Sportabout","Valiant"],[21,21,22.8,21.4,18.7,18.1],[6,6,4,6,8,6],[160,160,108,258,360,225],[110,110,93,110,175,105],[3.9,3.9,3.85,3.08,3.15,2.76],[2.62,2.875,2.32,3.215,3.44,3.46],[16.46,17.02,18.61,19.44,17.02,20.22],[0,0,1,1,0,1],[1,1,1,0,0,0],[4,4,4,3,3,3],[4,4,1,1,2,1]],"container":"<table class=\"display\">\n  <thead>\n    <tr>\n      <th> <\/th>\n      <th>mpg<\/th>\n      <th>cyl<\/th>\n      <th>disp<\/th>\n      <th>hp<\/th>\n      <th>drat<\/th>\n      <th>wt<\/th>\n      <th>qsec<\/th>\n      <th>vs<\/th>\n      <th>am<\/th>\n      <th>gear<\/th>\n      <th>carb<\/th>\n    <\/tr>\n  <\/thead>\n<\/table>","options":{"pageLength":4,"columnDefs":[{"className":"dt-right","targets":[1,2,3,4,5,6,7,8,9,10,11]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[4,10,25,50,100]}},"evals":[],"jsHooks":[]}</script>

---

.pull-left[
#### Here is an unordered list:

*   Item foo
*   Item bar
*   Item baz
*   Item zip
]

#### The markdown is:

.pull-left[
```markdown
 * Item foo
 * Item bar
```
]

---

.pull-left[

#### And an ordered list:
```markdown
1.  Item one
1.  Item two
1.  Item three
1.  Item four
```
]

.pull-right[

#### And an ordered list:

1.  Item one
1.  Item two
1.  Item three
1.  Item four
]

---

### And a nested list:

- level 1 item
  - level 2 item
  - level 2 item
    - level 3 item
    - level 3 item
- level 1 item
  - level 2 item
  - level 2 item
  - level 2 item
- level 1 item
  - level 2 item
  - level 2 item
- level 1 item

---

### Nesting an ol in ul in an ol

- level 1 item (ul)
  1. level 2 item (ol)
  1. level 2 item (ol)
    - level 3 item (ul)
    - level 3 item (ul)
- level 1 item (ul)
  1. level 2 item (ol)
  1. level 2 item (ol)
    - level 3 item (ul)
    - level 3 item (ul)
  1. level 4 item (ol)
  1. level 4 item (ol)
    - level 3 item (ul)
    - level 3 item (ul)
- level 1 item (ul)

---
# Images

![img](heart_rate_runs.png)
---

## Data Visualization

- ggplot is great for fast exploratory plots.
- It has great tools for creating plots for communicating your results.
- In this scenario, the emphasis should be on the __story__ you are trying to tell.

---
## Themes

- Branding [example from the BBC](https://bbc.github.io/rcookbook/#make_a_line_chart)

---
## Default theme

- Is called theme_grey()

```r
ggplot(diff_df, aes(x = pts_diff, y = win_pct)) +
  geom_point() + 
  theme_grey()
```

- Grey panel background
- white grid lines

---
## GGthemes

- package with some well known themes:
  - theme_fivethirtyeight()
  - theme_economist()
  
---
## Theme elements

- theme elements can be lines, text, etc.
- To specify an option, you use the corresponding element.

---
## Centering titles and subtitles

- When styling text, use element_text.

```r
theme(
  plot.title=element_text(hjust=.5)
)
```

---
## Grids

- When styling lines, use element_line

```r
theme(
  panel.grid.major=element_line(color="red")
)
```

---
## Labels

```r
plot <- nfl_stand %>% 
  mutate(
    color = case_when(
      season < 2020 & seed <= 6 ~ "blue",
      season == 2020 & seed <= 7 ~ "blue",
      TRUE ~  "red"
    )
  ) %>% 
  ggplot(aes(x = as.numeric(pts_diff), y = win_pct)) +
  geom_vline(xintercept = 0, size = 0.75, color = "#737373") +
  geom_point(
    aes(color = color),
    size = 3, alpha = 0.8
    ) +
  scale_color_identity() +
  labs(x = "Points Differential", y = "Win Percent",
       title = "Playoff teams typically have a positive point differential",
       subtitle = "Data through week 15 of the 2020 NFL Season",
       caption = "Plot: @thomas_mock | Data: ESPN")
```

---

```r
plot
```

---

## Scales

```r
plt_scales <- nfl_stand %>% 
  mutate(
    color = case_when(
      season < 2020 & seed <= 6 ~ "blue",
      season == 2020 & seed <= 7 ~ "blue",
      TRUE ~  "red"
    )
  ) %>% 
  ggplot(aes(x = as.numeric(pts_diff), y = win_pct)) +
  geom_vline(xintercept = 0, size = 0.75, color = "#737373") +
  geom_point(aes(color=color)) + 
  scale_color_identity()+
  scale_y_continuous(
    labels = scales::percent_format(accuracy = 1),
    breaks = seq(.0, 1, by = .10)
    ) +
  scale_x_continuous(
    breaks = seq(-200, 250, by = 50)
  ) +
  labs(x = "Points Differential", y = "Win Percent",
       title = "Playoff teams typically have a positive point differential",
       subtitle = "Data through week 15 of the 2020 NFL Season",
       caption = "Plot: @thomas_mock | Data: ESPN")
```

---

```r
plt_scales
```

---
## Experiment with themes

```r
plot + ggthemes::theme_economist()
```

## Final plot

```r
library(ggtext)

playoff_label_scatter <- tibble(
  pts_diff = c(25,-125), y = c(0.3, 0.8), 
  label = c("Missed<br>Playoffs", "Made<br>Playoffs"),
  color = c("#D50A0A", "#013369")
)

playoff_diff_plot <- nfl_stand %>% 
  mutate(
    pts_diff=as.numeric(pts_diff),
    color = case_when(
      season < 2020 & seed <= 6 ~ "#013369",
      season == 2020 & seed <= 7 ~ "#013369",
      TRUE ~  "#D50A0A"
    )
  ) %>% 
  ggplot(aes(x = pts_diff, y = win_pct)) +
  geom_vline(xintercept = 0, size = 0.75, color = "#737373") +
  geom_hline(yintercept = 0, size = 0.75, color = "#737373") +
  geom_point(
    aes(color = color),
    size = 3, alpha = 0.8
    ) +
  # ggtext::geom_richtext(
  #   data = playoff_label_scatter,
  #   aes(x = pts_diff, y = y, label = label, color = color),
  #   fill = "#f0f0f0", label.color = NA, # remove background and outline
  #   label.padding = grid::unit(rep(0, 4), "pt"), # remove padding
  #   family = "Chivo", hjust = 0.1, fontface = "bold",
  #   size = 8
  # ) +
  scale_color_identity() +
  labs(x = "Points Differential", y = "Win Percent",
       title = "Playoff teams typically have a positive point differential",
       subtitle = "Data through week 15 of the 2020 NFL Season",
       caption = str_to_upper("Plot: @thomas_mock | Data: ESPN")) +
  scale_y_continuous(
    labels = scales::percent_format(accuracy = 1),
    breaks = seq(.0, 1, by = .10)
    ) +
  scale_x_continuous(
    breaks = seq(-200, 250, by = 50)
  ) + 
  theme(plot.subtitle=element_text(hjust=.5))
```