36-315-Lec15

class: inverse, center, middle

# 36-315: Statistical Graphics and Visualization
## Lecture 15

Meghan Hall Department of Statistics & Data Science Carnegie Mellon University June 28, 2021

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layout: true
<div class="my-footer">cmu-36315.netlify.app</div>
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# Schedule

.large[Presentation sign-ups this AM]

.large[Lab 10 tomorrow, due Wednesday]
 
.medium[HW 5 due tomorrow]

.large[Last live lecture today]
 
.medium[Wednesday: special topics]

---

# What do you turn in?

.large[Final report: 11:30am EDT Friday]
 
.medium[.html]
 
.medium[.Rmd (don't forget `echo = FALSE` to suppress code)]

.large[Final presentation: right after]
 
.medium[.Rmd file only]
 
.medium[probably won't knit, that's fine! just to check]

---

# Today

.large[Adding another layer to our plots]
 
.medium[animation with `gganimate`]
 
.medium[interactivity with `plotly`]

.large[Functional programming with `purrr`]
 
.medium[`map` functions as an alternative to for loops]

---

# `gganimate`

.large[Adds animation to existing plots]
 
.medium[[https://gganimate.com/](https://gganimate.com/)]
 
.medium[using various `transition_*` functions]

.large[Many other options we won't discuss today]
 
.medium[can specify how data & aesthetics fade, change, etc.]

.large[Can run plots like usual or:]
 
.medium[use `anim_save("filepath")` to save as gif]
 
.medium[will save last-run animation]

---

# `gganimate`

.large[When should you *not* animate?]
 
.medium[when it doesn't add anything to the plot]

```r
penguins %>% 
  ggplot(aes(x = body_mass_g, y = bill_length_mm, color = species)) +
  geom_point(alpha = 0.7, size = 4) +
  scale_color_brewer(type = "qual", name = NULL) +
  labs(x = "Body Mass (g)",
       y = "Bill Length (mm)") +
  lab_theme() +
  theme(legend.position = c(0.8, 0.2),
        legend.text = element_text(size = 14),
        axis.title = element_text(size = 13))
```

---

# `gganimate`

---

# `gganimate`

.large[When should you *not* animate?]
 
.medium[when it doesn't add anything to the plot]

---

# `gganimate`

.center[![logo](figs/Lec15/scatter.gif)]

---

# `gganimate`

.large[When can you add animation?]
 
.medium[when it adds depth & emphasis to your story/conclusion]

```r
third_place %>%
  ggplot(aes(x = round, y = points, group = name, color = name)) +
  geom_line(size = 2) +
  scale_color_manual(values = c("#E0610E","#F596C8","#FFF500"),
                     name = NULL) +
  scale_x_continuous(breaks = seq(1, 17, 1)) +
  labs(title = "The race for third place in the 2020 F1 season",
       y = "Accumulated points", x = NULL) +
  lab_theme() +
  theme(legend.position = c(0.3, 0.7),
        panel.grid.major.x = element_blank(),
        legend.text = element_text(size = 13))
```

---

# `gganimate`

---

# `gganimate`

.large[When can you add animation?]
 
.medium[when it adds depth & emphasis to your story/conclusion]

```r
third_place %>%
  ggplot(aes(x = round, y = points, group = name, color = name)) +
  geom_line(size = 2) +
  scale_color_manual(values = c("#E0610E","#F596C8","#FFF500"),
                     name = NULL) +
  scale_x_continuous(breaks = seq(1, 17, 1)) +
  labs(title = "The race for third place in the 2020 F1 season",
       y = "Accumulated points",
       x = NULL) +
  lab_theme() +
  theme(legend.position = c(0.3, 0.7),
        panel.grid.major.x = element_blank(),
        legend.text = element_text(size = 13)) +
* transition_reveal(round)
```

---

# `gganimate`

.center[![logo](figs/Lec15/line-graph.gif)]

---

# `gganimate`

.large[When can you add animation?]
 
.medium[when it adds another useful dimension (usually time)]

```r
txhousing %>% 
  group_by(city, year) %>% 
  summarize(median = mean(median, na.rm = TRUE),
            listings = mean(listings, na.rm = TRUE)) %>% 
  ggplot(aes(x = median, y = listings, color = city == "Houston",
             size = city == "Houston")) +
  geom_point(show.legend = FALSE) +
  scale_color_manual(values = c("black","#bb0000")) +
  scale_size_manual(values = c(2, 4)) +
  scale_x_continuous(labels = dollar, name = "Median Price") +
  scale_y_continuous(labels = label_number_si()) +
  lab_theme() +
  labs(x = "Median Price", y = "Avg. of Monthly Listings",
       subtitle = "Houston in red")
```

---

# `gganimate`

---

# `gganimate`

.large[When can you add animation?]
 
.medium[when it adds another useful dimension (usually time)]

---

# `gganimate`

.center[![logo](figs/Lec15/scatter-year.gif)]

---

# `plotly`

.large[Adds interactivity (namely tooltips) to existing plots]
 
.medium[[https://plotly.com/ggplot2/](https://plotly.com/ggplot2/)]

.large[Assign your plot to an object]
 
.medium[and call within `ggplotly`]

---

# `plotly`

```r
scatter_plain <- penguins %>% 
 ggplot(aes(x = body_mass_g, y = flipper_length_mm, 
 color = species)) +
 geom_jitter(size = 3, alpha = 0.8) +
 scale_color_brewer(type = "qual", name = NULL) +
 labs(x = "Body Mass (g)", y = "Flipper Length (mm)") +
 lab_theme()
```

---

# `plotly`

```r
ggplotly(scatter_plain)
```

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---

# `plotly`

```r
scatter_sex <- penguins %>% 
 ggplot(aes(x = body_mass_g, y = flipper_length_mm, color = species,
* text = paste("sex:", sex))) +
 geom_jitter(size = 3, alpha = 0.8) +
 scale_color_brewer(type = "qual", name = NULL) +
 labs(x = "Body Mass (g)", y = "Flipper Length (mm)") +
 lab_theme()
```

---

# `plotly`

```r
ggplotly(scatter_sex, tooltip = c("text", "species"))
```

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---

# `plotly`

```r
scatter_more <- penguins %>% 
* mutate(`Body mass` = paste(body_mass_g, "grams"),
* `Flipper length` = paste0(flipper_length_mm, "mm")) %>%
 ggplot(aes(x = body_mass_g, y = flipper_length_mm, color = species,
* text = paste("sex:", sex), label = `Body mass`,
* label1 = `Flipper length`)) +
 geom_jitter(size = 3, alpha = 0.8) +
 scale_color_brewer(type = "qual", name = NULL) +
 labs(x = "Body Mass (g)",
 y = "Flipper Length (mm)") +
 lab_theme()
```

---

# `plotly`

```r
ggplotly(scatter_more, 
         tooltip = c("text", "species", "Body mass", "Flipper length"))
```

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---

# `plotly`

---

# `plotly`

```r
heat <- lincoln_weather %>% 
 select(CST, temp = `Max Temperature [F]`) %>% 
 mutate(date = ymd(CST), 
 month = month(date, label = TRUE),
 day = day(date),
* date_show = paste(month, day)) %>%
* ggplot(aes(x = month, y = day, text = date_show, fill = temp)) +
 geom_tile(color = "white") +
 scale_y_continuous(trans = "reverse", 
 breaks = seq(1, 31, 5)) + 
 labs(title = "Maximum temperature by day in Lincoln, NE in 2016") +
 scale_fill_scico(palette = "imola", 
 breaks = seq(20, 90, 10), 
 name = " °F") + 
 guides(fill = guide_colorsteps()) +
 theme(axis.ticks = element_blank(),
 panel.background = element_blank(),
 axis.title = element_blank(),
 axis.text = element_text(face = 2)) +
 coord_cartesian(expand = FALSE)
```

---

# `plotly`

```r
ggplotly(heat, tooltip = c("text", "temp"))
```

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---

# `purrr`

.large[Part of the `tidyverse`]
 
.medium[[https://purrr.tidyverse.org/](https://purrr.tidyverse.org/)]
 
.medium[[https://r4ds.had.co.nz/iteration.html#the-map-functions](https://r4ds.had.co.nz/iteration.html#the-map-functions)]

.large[Useful for *functional programming*]
 
.medium[provides an alternative to for loops]

.large[`map_*` functions allow you to iterate over elements]

---

# `purrr`

```r
class(penguins$bill_depth_mm)
```

```
## [1] "numeric"
```

```r
penguins %>% 
  map_chr(class)
```

```
##           species            island    bill_length_mm     bill_depth_mm 
##          "factor"          "factor"         "numeric"         "numeric" 
## flipper_length_mm       body_mass_g               sex              year 
##         "integer"         "integer"          "factor"         "integer"
```

```r
new_df <- penguins %>% 
 map_df(class)
```

---

# `purrr`

```r
penguins %>% 
  map_dbl(mean, na.rm = TRUE)
```

```
##           species            island    bill_length_mm     bill_depth_mm 
##                NA                NA          43.92193          17.15117 
## flipper_length_mm       body_mass_g               sex              year 
##         200.91520        4201.75439                NA        2008.02907
```

```r
penguins %>% 
  select_if(is.numeric) %>% 
  map_dbl(mean, na.rm = TRUE)
```

```
##    bill_length_mm     bill_depth_mm flipper_length_mm       body_mass_g 
##          43.92193          17.15117         200.91520        4201.75439 
##              year 
##        2008.02907
```

---

# `purrr`

.large[Very helpful for a very common task:]
 
.medium[split your data frame into pieces]
 
.medium[apply a function to perform an action on each piece]
 
.medium[put those pieces back together]

.large[The previous examples used known functions (`class`, `mean`)]
 
.medium[but we can also use user-defined functions]

---

# `purrr`

.center[Throughout the season, how did **Montreal's** standings points compare to the playoff threshold?]

.center[`nhl2021_games`]

.center[![logo](figs/Lec12/nhl_logo.png)]

---

# `purrr`

.center[`nhl2021_games`]

<table class="table" style="font-size: 16px; width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
 <tr>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> game_id </th>
 <th style="text-align:left;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> game_date </th>
 <th style="text-align:left;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> away_team </th>
 <th style="text-align:left;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> home_team </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> home_score </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> away_score </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> max_period </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:right;"> 2020020001 </td>
 <td style="text-align:left;"> 2021-01-13 </td>
 <td style="text-align:left;"> PIT </td>
 <td style="text-align:left;"> PHI </td>
 <td style="text-align:right;"> 6 </td>
 <td style="text-align:right;"> 3 </td>
 <td style="text-align:right;"> 3 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020002 </td>
 <td style="text-align:left;"> 2021-01-13 </td>
 <td style="text-align:left;"> CHI </td>
 <td style="text-align:left;"> T.B </td>
 <td style="text-align:right;"> 5 </td>
 <td style="text-align:right;"> 1 </td>
 <td style="text-align:right;"> 3 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020003 </td>
 <td style="text-align:left;"> 2021-01-13 </td>
 <td style="text-align:left;"> MTL </td>
 <td style="text-align:left;"> TOR </td>
 <td style="text-align:right;"> 5 </td>
 <td style="text-align:right;"> 4 </td>
 <td style="text-align:right;"> 4 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020004 </td>
 <td style="text-align:left;"> 2021-01-13 </td>
 <td style="text-align:left;"> VAN </td>
 <td style="text-align:left;"> EDM </td>
 <td style="text-align:right;"> 3 </td>
 <td style="text-align:right;"> 5 </td>
 <td style="text-align:right;"> 3 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020005 </td>
 <td style="text-align:left;"> 2021-01-13 </td>
 <td style="text-align:left;"> STL </td>
 <td style="text-align:left;"> COL </td>
 <td style="text-align:right;"> 1 </td>
 <td style="text-align:right;"> 4 </td>
 <td style="text-align:right;"> 3 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020006 </td>
 <td style="text-align:left;"> 2021-01-14 </td>
 <td style="text-align:left;"> WSH </td>
 <td style="text-align:left;"> BUF </td>
 <td style="text-align:right;"> 4 </td>
 <td style="text-align:right;"> 6 </td>
 <td style="text-align:right;"> 3 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020007 </td>
 <td style="text-align:left;"> 2021-01-14 </td>
 <td style="text-align:left;"> BOS </td>
 <td style="text-align:left;"> N.J </td>
 <td style="text-align:right;"> 2 </td>
 <td style="text-align:right;"> 3 </td>
 <td style="text-align:right;"> 5 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020008 </td>
 <td style="text-align:left;"> 2021-01-14 </td>
 <td style="text-align:left;"> NYI </td>
 <td style="text-align:left;"> NYR </td>
 <td style="text-align:right;"> 0 </td>
 <td style="text-align:right;"> 4 </td>
 <td style="text-align:right;"> 3 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020009 </td>
 <td style="text-align:left;"> 2021-02-22 </td>
 <td style="text-align:left;"> DAL </td>
 <td style="text-align:left;"> FLA </td>
 <td style="text-align:right;"> 3 </td>
 <td style="text-align:right;"> 1 </td>
 <td style="text-align:right;"> 3 </td>
 </tr>
 <tr>
 <td style="text-align:right;"> 2020020010 </td>
 <td style="text-align:left;"> 2021-01-14 </td>
 <td style="text-align:left;"> CAR </td>
 <td style="text-align:left;"> DET </td>
 <td style="text-align:right;"> 0 </td>
 <td style="text-align:right;"> 3 </td>
 <td style="text-align:right;"> 3 </td>
 </tr>
</tbody>
</table>

---

# `purrr`

```r
north_div <- nhl2021_games %>% 
 mutate(winner = ifelse(home_score > away_score, "home", "away")) %>% 
 pivot_longer(home_team:away_team,
 names_to = c("home_away", ".value"),
 names_pattern = "(.+)_(.+)") %>% 
 mutate(points = case_when(winner == home_away ~ 2,
 winner != home_away & max_period > 3 ~ 1,
 TRUE ~ 0)) %>% 
 filter(team %in% c("WPG", "EDM", "CGY", "VAN", "MTL",
 "OTT", "WPG", "TOR")) %>% 
 arrange(game_date)
```

---

# `purrr`

```r
north_total <- north_div %>% 
 group_by(team) %>% 
 mutate(total_points = cumsum(points)) %>% 
 summarize(total_points = max(total_points)) %>% 
 arrange(desc(total_points))
```

---

# `purrr`

```r
north_total %>% 
* ggplot(aes(x = team, y = total_points, fill = team == "MTL")) +
  geom_bar(stat = "identity", show.legend = FALSE) +
* scale_fill_manual(values = c("dark grey", "#AF1E2D")) +
* geom_hline(yintercept = pluck(north_total, 2, 4),
             color = "black", size = 2) +
  labs(x = NULL, y = "Standings points",
       title = "Montreal's standings points, 2021 season",
       subtitle = "Compared to playoffs threshold in black") +
  lab_theme()
```

---

# `purrr`

---

# `purrr`

Start with an example: what was the status as of April 1?

```r
north_div %>% 
 filter(game_date <= "2021-04-01") %>% 
 mutate(game_date = "2021-04-01") %>% 
 group_by(team, game_date) %>% 
 mutate(total_points = cumsum(points)) %>% 
 summarize(total_points = max(total_points)) %>% 
 arrange(desc(total_points)) %>% 
 ungroup() %>% 
 mutate(rank = row_number(), 
 threshold = ifelse(rank == 4, total_points, NA))
```

<table class="table" style="font-size: 16px; width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
 <tr>
 <th style="text-align:left;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> team </th>
 <th style="text-align:left;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> game_date </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> total_points </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> rank </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> threshold </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:left;"> TOR </td>
 <td style="text-align:left;"> 2021-04-01 </td>
 <td style="text-align:right;"> 49 </td>
 <td style="text-align:right;"> 1 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> WPG </td>
 <td style="text-align:left;"> 2021-04-01 </td>
 <td style="text-align:right;"> 46 </td>
 <td style="text-align:right;"> 2 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> EDM </td>
 <td style="text-align:left;"> 2021-04-01 </td>
 <td style="text-align:right;"> 45 </td>
 <td style="text-align:right;"> 3 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> MTL </td>
 <td style="text-align:left;"> 2021-04-01 </td>
 <td style="text-align:right;"> 41 </td>
 <td style="text-align:right;"> 4 </td>
 <td style="text-align:right;"> 41 </td>
 </tr>
 <tr>
 <td style="text-align:left;"> CGY </td>
 <td style="text-align:left;"> 2021-04-01 </td>
 <td style="text-align:right;"> 35 </td>
 <td style="text-align:right;"> 5 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> VAN </td>
 <td style="text-align:left;"> 2021-04-01 </td>
 <td style="text-align:right;"> 35 </td>
 <td style="text-align:right;"> 6 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> OTT </td>
 <td style="text-align:left;"> 2021-04-01 </td>
 <td style="text-align:right;"> 28 </td>
 <td style="text-align:right;"> 7 </td>
 <td style="text-align:right;"> </td>
 </tr>
</tbody>
</table>

---

# `purrr`

Create the function with the game date as the argument

```r
points_by_day <- function(day) {
 
 north_div %>% 
 filter(game_date <= day) %>% 
 mutate(game_date = day) %>% 
 group_by(team, game_date) %>% 
 mutate(total_points = cumsum(points)) %>% 
 summarize(total_points = max(total_points)) %>% 
 arrange(desc(total_points)) %>% 
 ungroup() %>% 
 mutate(rank = row_number(), 
 threshold = ifelse(rank == 4, total_points, NA))
 
}
```

---

# `purrr`

Apply the function with `map_df`: apply the `points_by_day` function to every unique value of `game_date` from `north_div`

```r
points_by_day_df <- 
 map_df(unique(north_div$game_date), points_by_day)
```

That df has the following for every game day:

<table class="table" style="font-size: 16px; width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
 <tr>
 <th style="text-align:left;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> team </th>
 <th style="text-align:left;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> game_date </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> total_points </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> rank </th>
 <th style="text-align:right;font-weight: bold;color: white !important;background-color: #bb0000 !important;"> threshold </th>
 </tr>
 </thead>
<tbody>
 <tr>
 <td style="text-align:left;"> TOR </td>
 <td style="text-align:left;"> 2021-03-01 </td>
 <td style="text-align:right;"> 36 </td>
 <td style="text-align:right;"> 1 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> EDM </td>
 <td style="text-align:left;"> 2021-03-01 </td>
 <td style="text-align:right;"> 28 </td>
 <td style="text-align:right;"> 2 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> WPG </td>
 <td style="text-align:left;"> 2021-03-01 </td>
 <td style="text-align:right;"> 27 </td>
 <td style="text-align:right;"> 3 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> MTL </td>
 <td style="text-align:left;"> 2021-03-01 </td>
 <td style="text-align:right;"> 23 </td>
 <td style="text-align:right;"> 4 </td>
 <td style="text-align:right;"> 23 </td>
 </tr>
 <tr>
 <td style="text-align:left;"> CGY </td>
 <td style="text-align:left;"> 2021-03-01 </td>
 <td style="text-align:right;"> 22 </td>
 <td style="text-align:right;"> 5 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> VAN </td>
 <td style="text-align:left;"> 2021-03-01 </td>
 <td style="text-align:right;"> 20 </td>
 <td style="text-align:right;"> 6 </td>
 <td style="text-align:right;"> </td>
 </tr>
 <tr>
 <td style="text-align:left;"> OTT </td>
 <td style="text-align:left;"> 2021-03-01 </td>
 <td style="text-align:right;"> 17 </td>
 <td style="text-align:right;"> 7 </td>
 <td style="text-align:right;"> </td>
 </tr>
</tbody>
</table>

---

# `gganimate`

Use this new df with a `transition_manual` layer to create the animation

```r
*points_by_day_df %>%
  ggplot(aes(x = team, y = total_points, fill = team == "MTL")) +
  geom_bar(stat = "identity", show.legend = FALSE) +
  scale_fill_manual(values = c("dark grey", "#AF1E2D")) +
* geom_hline(aes(yintercept = threshold),
             color = "black", size = 2) +
  labs(x = NULL, y = "Standings points",
*      title = "Montreal's standings points: {current_frame}",
       subtitle = "Compared to playoffs threshold in black") +
  lab_theme() +
  theme(panel.grid.major.x = element_blank()) +
* transition_manual(game_date)
```

---

# `gganimate`

.center[![logo](figs/Lec15/MTL_pts.gif)]

---

# Upcoming

.large[Homework 5 due Tuesday]

.large[Lab 10 due Wednesday]

.large[Final reports due 11:30am EDT Friday]
 
.medium[no matter when your presentation is]