07 - Plots, Graphics, and tables

Layout

::: {#fig-dogs layout-ncol=2}

![Sleeping](images/boston-sleep.png){#fig-sleep}

![Happy](images/boston-terrier.png){#fig-awake}

The two states of Howard.

:::

Layout

Figure panels

::: {layout-ncol=2}
![Howard on a couch](images/howard-comfy.png)

![Howard in a table](images/howard-table.png)
:::

Multiple rows

::: {layout-nrow=2}
![Howard on a couch](images/howard-comfy.png)

![Howard in a table](images/howard-table.png)

![Howard sleeping](images/boston-sleep.png)

![Howard awake](images/boston-terrier.png)
:::

Figure divs

You can treat any markdown content you want as a figure by enclosing it in Pandoc div block with an identifier prefaced with #fig-. For example, here we create a figure that includes an embedded iframe:

::: {#fig-elephant}

<iframe width="560" height="315" src="https://www.youtube.com/embed/SNggmeilXDQ"></iframe>

Elephant
:::

Figure 2: Elephant

Your Turn

Open materials/workshop/07-static/figure-layout
Swap between row and col layout

Custom Layouts

Read [[1,1], [1]] as:

Row 1: two equal sized images each taking up half of the column

Row 2: one image, taking up the entire column

::: {layout="[[1,1], [1]]"}
![Howard sleeping](images/boston-sleep.png)

![Howard in a table](images/howard-table.png)

![Howard on a couch](images/howard-comfy.png)
:::

Custom Layouts

Read "[[70,30], [100]]" as:

Row 1: two images, taking up 70% and 30% of the column

Row 2: one image, taking up 100% of column

::: {layout="[[70,30], [100]]"}

![Howard on a couch](images/howard-comfy.png)

![Howard sleeping](images/boston-sleep.png)

![Howard in a table](images/howard-table.png)
:::

Custom layouts

You can also add negative values for “blank space”

[[40,-20,40], [100]]

Row 1: 40% image 1, 20% blank, 40% image 2

Row 2: 100% image 3

::: {layout="[[40,-20,40], [100]]"}
![Howard on a couch](images/howard-comfy.png)

![Howard sleeping](images/boston-sleep.png)

![Howard in a table](images/howard-table.png)
:::

Custom layouts, vertical

If images within a row are of differing heights, you can control vertical alignment.

{layout="[25,-2,10]" layout-valign="bottom"}

Row: 25

::: {layout="[25,-2,10]" layout-valign="bottom"}
![Howard on a couch](images/howard-comfy.png)

![Howard in a table](images/howard-table.png)
:::

Your Turn

Open materials/workshop/07-visuals/figure-layout2.qmd

```{r}
#| eval: false
#| layout-ncol: 2
#| fig-cap:
#|   - "Speed and Stopping Distances of Cars"
#|   - "Engine displacement and fuel efficiency in Cars"

cars |> 
  ggplot(aes(x = speed, y = dist)) +
  geom_point()

mtcars |> 
  ggplot(aes(x = disp, y = mpg)) +
  geom_point()
```

Figure layout, subcaptions

Code
Output

```{r}
#| eval: false
#| label: fig-charts
#| fig-cap: Charts
#| fig-subcap:
#|   - "Cars"
#|   - "mtcars"
#| layout-ncol: 2

cars |> 
  ggplot(aes(x = speed, y = dist)) +
  geom_point()

mtcars |> 
  ggplot(aes(x = disp, y = mpg)) +
  geom_point()
```

Figure 3: Charts

Figure layout, custom

Code
Output

```{r}
#| eval: false
#| layout: [[45,-10, 45], [100]]

cars |> 
  ggplot(aes(x = speed, y = dist)) +
  geom_point()

mtcars |> 
  ggplot(aes(x = disp, y = mpg)) +
  geom_point()

mtcars |> 
  ggplot(aes(x = cyl, y = mpg, group = cyl, color = factor(cyl))) +
  geom_boxplot() +
  geom_jitter()
```

Your Turn

Open materials/workshop/07-visuals/plot-layout.qmd
Explore, try it out and render

Block layout, arbitrary content

::: {layout-ncol=2}
## List One

- Item A
- Item B
- Item C

## List Two

- Item X
- Item Y
- Item Z
:::

Block layout, arbitrary content

List One

Item A
Item B
Item C

List Two

Item X
Item Y
Item Z

Block layout, arbitrary content

::: {layout-ncol=2}
- Item X
- Item Y
- Item Z

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Curabitur gravida eu erat et fring. Morbi congue augue vel eros ullamcorper, eget convallis tortor sagittis. Fusce sodales viverra mauris a fringilla. Donec feugiat, justo eu blandit placerat, enim dui volutpat turpis, eu dictum lectus urna eu urna. Mauris sed massa ornare, interdum ipsum a, semper massa. 
:::

Block layout, arbitrary content

Item X
Item Y
Item Z

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Curabitur gravida eu erat et fring. Morbi congue augue vel eros ullamcorper, eget convallis tortor sagittis. Fusce sodales viverra mauris a fringilla. Donec feugiat, justo eu blandit placerat, enim dui volutpat turpis, eu dictum lectus urna eu urna. Mauris sed massa ornare, interdum ipsum a, semper massa.

Grid, custom layout

The “grid” layout in Quarto is 12 units wide - you can break up the grid into different subsections as long as they add up to 12.

This column takes 1/3 of the page

This column takes 2/3 of the page

::: {.grid}

::: {.g-col-4}
This column takes 1/3 of the page
![](boston-terrier.png)
:::

::: {.g-col-8}
This column takes 2/3 of the page
![](boston-sleep.png)
:::

:::

Your Turn

Try out the grid layout in the previous slide, modifying the .g-col-8 to add up to a total of 12
Create a new Quarto doc

Article Layout

Quarto supports a variety of page layout options that enable you to author content that:

Fills the main content region .column-body
Overflows the content region .column-body-outset
Spans the entire page .column-page
Occupies the document margin .column-margin

Put it in a div, and assign a specific class

:::{.column-body-outset}
Outset content...
:::

:::{.column-margin}
Margin/aside figure
:::

Your Turn

Open materials/workshop/07-visuals/plots.qmd
Try modifying the layout with ::: {.column-???} syntax

`ggplot2`

library(palmerpenguins)
library(ggplot2)
ggplot2::theme_set(ggplot2::theme_minimal())
penguins <- na.omit(penguins)

`ggplot2`

mass_flipper <- ggplot(data = penguins, 
                       aes(x = flipper_length_mm,
                           y = body_mass_g)) +
  geom_point(aes(color = species, 
                 shape = species),
             size = 3,
             alpha = 0.8) +
  scale_color_manual(values = c("darkorange","purple","cyan4")) +
  labs(title = "Penguin size, Palmer Station LTER",
       subtitle = "Flipper length and body mass for Adelie, Chinstrap and Gentoo Penguins",
       x = "Flipper length (mm)",
       y = "Body mass (g)",
       color = "Penguin species",
       shape = "Penguin species") +
  theme(legend.position = c(0.2, 0.7),
        plot.title.position = "plot",
        plot.caption = element_text(hjust = 0, face= "italic"),
        plot.caption.position = "plot")

`ggplot2`

mass_flipper

`ggplot2`

```{r}
#| fig-height: 2
mass_flipper
```

`ggplot2`

```{r}
#| fig-height: 4
#| fig-dpi: 600
mass_flipper
```

`ggplot2`

```{r}
#| fig-height: 10
#| fig-dpi: 600
mass_flipper
```

`ggplot2`

```{r}
#| fig-height: 10
#| fig-width: 16
#| fig-dpi: 400
mass_flipper
```

`ggplot2`

```{r}
#| fig-align: center
mass_flipper
```

Interactivity

Quarto supports JupyterWidgets (with Jupyter) or htmlwidgets in R/knitr

library(leaflet)
leaflet() %>%
  addTiles() %>%  # Add default OpenStreetMap map tiles
  addMarkers(lng=-77.0168, lat=38.7814, popup="You are here - in Maryland!")

Observable.js

Quarto includes native support for Observable JS, a set of enhancements to vanilla JavaScript created by Mike Bostock (also the author of D3). Observable JS is distinguished by its reactive runtime, which is especially well suited for interactive data exploration and analysis.

viewof bill_length_min = Inputs.range(
  [32, 50], 
  {value: 35, step: 1, label: "Bill length (min):"}
)
viewof islands = Inputs.checkbox(
  ["Torgersen", "Biscoe", "Dream"], 
  { value: ["Torgersen", "Biscoe"], 
    label: "Islands:"
  }
)

Plot
Data

Plot.rectY(filtered, 
  Plot.binX(
    {y: "count"}, 
    {x: "body_mass", fill: "species", thresholds: 20}
  ))
  .plot({
    facet: {
      data: filtered,
      x: "sex",
      y: "species",
      marginRight: 80
    },
    marks: [
      Plot.frame(),
    ]
  }
)

Inputs.table(filtered)

data = FileAttachment("palmer-penguins.csv").csv({ typed: true })

filtered = data.filter(function(penguin) {
  return bill_length_min < penguin.bill_length &&
         islands.includes(penguin.island);
})

`ggiraph`

Example from Claus Wilke

library(tidyverse)
library(sf)
library(ggiraph)
library(glue)
library(cowplot)

texas_income <- readRDS(url("https://wilkelab.org/SDS375/datasets/Texas_income.rds")) %>%
  select(-county)
US_census <- read_csv("https://wilkelab.org/SDS375/datasets/US_census.csv")
tx_census <- US_census %>% 
  filter(state == "Texas") %>%
  select(FIPS, name, pop2010, area) %>%
  extract(name, "county", regex = "(.+) County") %>%
  mutate(
    FIPS = as.character(FIPS),
    popratio = pop2010/median(pop2010),
  )
texas_counties <- left_join(texas_income, tx_census, by = "FIPS")

`ggiraph`

texas_scatter <- texas_counties %>%
  ggplot(aes(pop2010, median_income)) +
  geom_point_interactive(
    aes(
      tooltip = county,
      data_id = county
    ),
    na.rm = TRUE, size = 3
  ) +
  scale_x_log10() +
  theme_bw()
# then make the map
texas_county_map <- texas_counties %>%
  ggplot() +
  geom_sf_interactive(
    aes(
      tooltip = county,
      data_id = county
    ),
    size = 0.2, color = "black"
  ) +
  theme_void()

girafe(
  ggobj = plot_grid(texas_scatter, texas_county_map),
  width_svg = 6,
  height_svg = 3
)

`ggiraph`

Tables

`gt` + `gtExtras`

With the gt package, anyone can make wonderful-looking tables using the R programming language. The gt philosophy: we can construct a wide variety of useful tables with a cohesive set of table parts. These include the table header, the stub, the column labels and spanner column labels, the table body, and the table footer.

`gt`, a Grammar of Tables

`gt`

library(dplyr, warn.conflicts = FALSE)
library(gt)
library(gtExtras)
library(gtsummary)

head(mtcars) |> 
  gt() |> 
  tab_options(
    table.font.size = px(40), #< because I've made the slides a lot bigger
    column_labels.font.size = px(45) #< normally don't have to increase this
  )

mpg	cyl	disp	hp	drat	wt	qsec	vs	am	gear	carb
21.0	6	160	110	3.90	2.620	16.46	0	1	4	4
21.0	6	160	110	3.90	2.875	17.02	0	1	4	4
22.8	4	108	93	3.85	2.320	18.61	1	1	4	1
21.4	6	258	110	3.08	3.215	19.44	1	0	3	1
18.7	8	360	175	3.15	3.440	17.02	0	0	3	2
18.1	6	225	105	2.76	3.460	20.22	1	0	3	1

`gt` extension packages

`gtExtras`

gtExtras provides additional helper functions to gt, mainly themes and inline plotting

`gtsummary`

gtsummary extends gt to descriptive statistics and statistical summaries of models

`gtsummary`

Comes with built in example datasets like trial

trial2 <- trial %>% dplyr::select(trt, age, grade)
dplyr::glimpse(trial2)

Rows: 200
Columns: 3
$ trt   <chr> "Drug A", "Drug B", "Drug A", "Drug A", "Drug A", "Drug B", "Dru…
$ age   <dbl> 23, 9, 31, NA, 51, 39, 37, 32, 31, 34, 42, 63, 54, 21, 48, 71, 3…
$ grade <fct> II, I, II, III, III, I, II, I, II, I, III, I, III, I, I, III, II…

trial2 %>% tbl_summary(by = trt) %>% add_p()

Characteristic	Drug A, N = 98¹	Drug B, N = 102¹	p-value²
Age	46 (37, 59)	48 (39, 56)	0.7
Unknown	7	4
Grade			0.9
I	35 (36%)	33 (32%)
II	32 (33%)	36 (35%)
III	31 (32%)	33 (32%)
¹ Median (IQR); n (%)
² Wilcoxon rank sum test; Pearson's Chi-squared test

Create a summary

penguins <- palmerpenguins::penguins

penguin_sum <- penguins |>
  na.omit() |>
  group_by(species, sex) |>
  summarise(
    n = n(),
    bill_len = mean(bill_length_mm),
    plt_bill = list(bill_length_mm),
    mass = mean(body_mass_g),
    plt_mass = list(body_mass_g),
    .groups = "drop"
  ) |> 
  arrange(species, desc(bill_len))

penguin_sum

# A tibble: 6 × 7
  species   sex        n bill_len plt_bill    mass plt_mass  
  <fct>     <fct>  <int>    <dbl> <list>     <dbl> <list>    
1 Adelie    male      73     40.4 <dbl [73]> 4043. <int [73]>
2 Adelie    female    73     37.3 <dbl [73]> 3369. <int [73]>
3 Chinstrap male      34     51.1 <dbl [34]> 3939. <int [34]>
4 Chinstrap female    34     46.6 <dbl [34]> 3527. <int [34]>
5 Gentoo    male      61     49.5 <dbl [61]> 5485. <int [61]>
6 Gentoo    female    58     45.6 <dbl [58]> 4680. <int [58]>

`gtExtras`

```{r}
#| output-location: slide
#| fig-width: 10
gt(penguin_sum) |>
  gt_plt_dist(
    plt_bill, 
    line_color = "#447099", 
    fill = "#75aadb",
    fig_dim = c(15, 50)
    ) |> 
  gt_plt_dist(
    plt_mass, 
    line_color = "#447099", 
    fill = "#75aadb"
    ) |> 
  gt_add_divider(
    c(bill_len, mass), "left", 
    weight = px(1), color = "#d3d3d3"
    ) |> 
  cols_align("left", species) |> 
  text_transform(
    cells_body(sex),
    fn = function(x){
      sex_planet <- ifelse(x == "male", "mars", "venus")
      
      purrr::map(
        sex_planet, 
        ~fontawesome::fa(
          .x, height = "45px",
          fill = ifelse(.x =="mars", "#7fbf7b", "#af8dc3")))
                 }) |>
  gt_theme_nytimes() |>
  tab_options(data_row.padding = px(2),
              table.font.size = px(40),
              column_labels.font.size = px(35))
```

`gtExtras`

species	n	bill_len	mass
Adelie	73	40.39041	4043.493
Adelie	73	37.25753	3368.836
Chinstrap	34	51.09412	3938.971
Chinstrap	34	46.57353	3527.206
Gentoo	61	49.47377	5484.836
Gentoo	58	45.56379	4679.741

`gtExtras`

Original: https://twitter.com/thomas_mock/status/1442541043019390982?s=20&t=0JewnMHkYrfPrYosfE2XIg

party_df <- tibble(
  Party = c("SPD", "CDU/CSU", "Greens", "FDP", "AfD", "Left", "Other"),
  Seats = c(206, 196, 118, 92, 83, 39, 1),
  `% of 2nd Votes` = c(25.7, 24.1, 14.8, 11.5, 10.3, 4.9, 8.7)
)

minimal_table <- gt(party_df) %>% 
  gtExtras::gt_plt_dot(column = Seats, category_column = Party,  max_value = 379,
    palette = c("#ec323f", "black", "#63d64a", "#fff24e", "#4fabf7", "#e956ad", "grey")) %>% 
  gtExtras::gt_theme_nytimes() %>% 
  gt::tab_header(title = "Results by Party in the Bundestag Election",
             subtitle = "Seats and votes are based on provisional official results.") %>% 
  gt::cols_width(Party ~ px(300), 3 ~ px(30))

`gtExtras`

Your Turn

Open materials/workshop/07-static/gt-summary.qmd
Open materials/workshop/07-static/stat-html.qmd
Explore and render

07 - Plots, Graphics, and tables

Layout

Layout

Figure panels

Multiple rows

Figure divs

Your Turn

Custom Layouts

Custom Layouts

Custom layouts

Custom layouts, vertical

Your Turn

Figure layout

Figure layout, subcaptions

Figure layout, custom

Your Turn

Block layout, arbitrary content

Block layout, arbitrary content

Block layout, arbitrary content

Block layout, arbitrary content

Grid, custom layout

Your Turn

Article Layout

Your Turn

ggplot2

ggplot2

ggplot2

ggplot2

ggplot2

ggplot2

ggplot2

ggplot2

Interactivity

Observable.js

ggiraph

ggiraph

ggiraph

Tables

gt + gtExtras

gt, a Grammar of Tables

gt

gt extension packages

gtExtras

gtsummary

gtsummary

Create a summary

gtExtras

gtExtras

gtExtras

gtExtras

Your Turn

`ggplot2`

`ggplot2`

`ggplot2`

`ggplot2`

`ggplot2`

`ggplot2`

`ggplot2`

`ggplot2`

`ggiraph`

`ggiraph`

`ggiraph`

`gt` + `gtExtras`

`gt`, a Grammar of Tables

`gt`

`gt` extension packages

`gtExtras`

`gtsummary`

`gtsummary`

`gtExtras`

`gtExtras`

`gtExtras`

`gtExtras`