Data Visualization

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.title[
# Data Visualization
]
.subtitle[
## Chapter 2. The Grammar of Graphs in R
]
.author[
### Iñaki Úcar
]
.institute[
### Department of Statistics | uc3m-Santander Big Data Institute
]
.institute[
### Master in Computational Social Science
]
.date[
### Licensed under Creative Commons Attribution <a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a> Last generated: 2023-11-14
]

---

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---
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# Building Graphs Layer by Layer

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# An Object-Oriented Graphics System

.footnote[Wilkinson, L. (2005) _**The grammar of graphics**_. Springer New York.]

- Graphics are collections of **objects** that follow a set of rules, a **grammar**,
  so that they behave consistently and flexibly.

- The specification of the formal language is expressed in six statements:
  1. **DATA**: a set of data operations that create variables from datasets,
  2. **TRANS**: variable transformations (e.g., rank),
  3. **SCALE**: scale transformations (e.g., log),
  4. **COORD**: a coordinate system (e.g., polar),
  5. **ELEMENT**: marks (e.g., points) and their aesthetic attributes (e.g., color),
  6. **GUIDE**: one or more guides (axes, legends, etc.).

- These components link data to (visual) objects and specify a scene containing those.

---

# An Object-Oriented Graphics System

.center[![:scale 85%](assets/img/ch2/specification-example.png)]

---

# An Object-Oriented Graphics System

.center[![:scale 100%](assets/img/ch2/specification-tree.png)]

---
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# About ggplot2

- An R package for producing statistical graphics

- Underlying grammar based on the **Grammar of Graphics** (thus GG)

- Instead of being limited to sets of pre-defined graphics, 
  it allows to **compose** graphs by combining (adding, `+`) components

- Simple set of core principles (+ some very few special cases)

- Carefully chosen defaults

- Good for **quick prototyping**, designed to work iteratively

- But also **publication-quality graphics**, with a comprehensive theming system

- Lots of [extensions](https://exts.ggplot2.tidyverse.org/)!

---
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# ggplot2 Basics

- Requires [**tidy data**](https://vita.had.co.nz/papers/tidy-data.html):
  1 observation per row, 1 variable per column:

|country   |continent | year| lifeExp|      pop|  gdpPercap|
|:---------|:---------|----:|-------:|--------:|----------:|
|Mauritius |Africa    | 1962|  60.246|   701016|  2529.0675|
|Indonesia |Asia      | 1957|  39.918| 90124000|   858.9003|
|Italy     |Europe    | 1977|  73.480| 56059245| 14255.9847|

- All plots are composed of **data** and **mapping**, the description of how
  data attributes are mapped to **aes**thetic attributes (channels).

- Basic workflow:

```r
ggplot(data) + # create the graphic object with the data
  aes(x=..., y=..., color=...) + # add the general mapping
  ... # add more components (geoms, scales, coords, facets, themes...)
```

---
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# ggplot2 Basics

There are five types of components:

- A _layer_ is a collection of **geom**etric elements (points, lines...)
  and **stat**istical transformations (binning, counting...).

- A **scale** controls a channel, adds or modifies how attributes are mapped
  (position, color, shape, size...).

- A **coord**inate system describes how data coordinates are mapped to
  the plane of the graphic. It also provides axes and gridlines.

- A **facet** specifies how to break up and display subsets of data as small
  multiples (AKA _conditioning_, _latticing_ or _tresllising_).

- A **theme** controls the finer points of display to create attractive plots
  (background, fonts, guide aspect and positioning...).

---
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# Tutorial 01
## [Building Graphs Layer by Layer](../tutorials/01/)

---

# Aesthetics Specification

.footnote[Read the comprehensive [guide on aesthetics](https://ggplot2.tidyverse.org/articles/ggplot2-specs.html).]

.font120[
- Mastering data **mappings** is an important (the most important?) skill.
]

.font120[
- Each **geom** is affected by **a different set of aesthetics**:
]

.pull-left[
From `?geom_point` (required in bold):

> - **`x`**
> - **`y`**
> - `alpha`
> - `colour`
> - .blue[`fill`]
> - `group`
> - .red[`shape`]
> - `size`
> - .blue[`stroke`]
]

.pull-right[
From `?geom_line` (required in bold):

> - **`x`**
> - **`y`**
> - `alpha`
> - `colour`
> - `group`
> - .red[`linetype`]
> - `size`
]

---

# Individual Geoms

| Geom | Result | Details |
|---|---|---|
| `geom_point()` `geom_text()` `geom_label()` | **scatterplot** | Understands `shape`. Helper for text. Helper for labels. |
| `geom_line()` `geom_path()` `geom_step()` `geom_function()` | **line plot** | Connects points from left to right, understands `linetype`. Connects points in order. Produces a _stairstep_ plot. Connects points of a given function of`x`. |
| `geom_bar()` `geom_col()` | **bar chart** | `stat="count"` by default! Multiple bars are stacked by default. |
| `geom_area()` | **area plot** | Line plot filled from 0 to `y`. |
| `geom_polygon()` | | Filled path. |
| `geom_rect()` `geom_tile()` `geom_raster()` | | Rectangle by `xmin`, `xmax`, `ymin`, `ymax`. Rectangle by center (`x`, `y`) and size (`width`, `height`). Faster tiles with constant size. |

---

# Individual Geoms

- Two dimensional: require `x` and `y`, understand `color` and `size`.
- Some of them can be `fill`ed.

---

# Collective Geoms

- Dealing with point overplotting

| Geom | Result | Details |
|---|---|------|
| `geom_jitter()` `geom_count()` `geom_bin_2d()` `geom_hex()` | | `geom_point()`, but adds some jitter to each point. Maps the count of overlapping points to `size`. Maps the count of rectangles to `fill`. Same, but using hexagons. |

---

# Collective Geoms

- Dealing with uncertainty

| Geom | Result | Details |
|---|---|------|
| `geom_pointrange()` `geom_linerange()` `geom_errorbar()` `geom_crossbar()` | | Various ways of representing a vertical intervals defined by `x`, `ymin` and `ymax`. |
| `geom_ribbon()` | | Special case of `geom_area()` with `ymin` too. |

---

# Collective Geoms

- Arbitrary segments

| Geom | Result | Details |
|---|---|------|
| `geom_segment()` `geom_curve()` `geom_spoke()` | | Straight line between points (`x`, `y`) and (`xend`, `yend`). Same, but curved line. Polar parametrization of `geom_segment()`. |

---

# Collective Geoms

- Distributions

| Geom | Result | Details |
|---|---|------|
| `geom_histogram()` `geom_freqpoly()` `geom_dotplot()` | **histogram** | Distribution of a continuous variable by bins. To display the counts with lines instead. Histograms of stacked dots. |
| `geom_density()` | **density plot** | Smoothed version of the histogram. |
| `geom_rug()` | | Draws ticks for marginal distributions. |

---

# Collective Geoms

- Boxplots

| Geom | Result | Details |
|---|---|------|
| `geom_boxplot()` `geom_violin()` | **boxplot** | Compact display of the distribution of a continuous variable. Mirrored density, displayed as a boxplot. |

---

# Collective Geoms

- Smoothing lines

| Geom | Result | Details |
|---|---|------|
| `geom_smooth()` `geom_quantile()` | | Fits a model and draws a smoothing line. Fits a quantile regression and draws the quantiles. |

---

# Collective Geoms

- Contours

| Geom | Result | Details |
|---|---|------|
| `geom_contour()` `geom_contour_filled()` `geom_density_2d` `geom_density_2d_filled()` | **contour plot** | 2D contours of 3D surfaces of regular `x`, `y`. Filled version. 2D contours after computing the density. Filled version. |

---

# Collective Geoms

- Maps

| Geom | Result | Details |
|---|---|------|
| `geom_map()` `geom_sf()` `geom_sf_text()` `geom_sf_label()` | **map** | Old way to plot polygons as a map. Current recommended way via `sf`. Similar to `geom_text()` but for `sf`. Similar to `geom_label()` but for `sf`. |

---

# Geom vs. Stat

.pull-left[

```r
ggplot(mpg, aes(displ, hwy)) +
* geom_point(stat="identity")
```

<img src="ch2_files/figure-html/stat-identity-1-1.png" style="display: block; margin: auto;" />
]
.pull-right[

```r
ggplot(mpg, aes(displ, hwy)) +
* stat_identity(geom="point")
```

<img src="ch2_files/figure-html/stat-identity-2-1.png" style="display: block; margin: auto;" />
]

---

# Geom vs. Stat

.pull-left[

```r
ggplot(mpg, aes(hwy)) +
* geom_bar(stat="count")
```

<img src="ch2_files/figure-html/stat-count-1-1.png" style="display: block; margin: auto;" />
]
.pull-right[

```r
ggplot(mpg, aes(hwy)) +
* stat_count(geom="bar")
```

<img src="ch2_files/figure-html/stat-count-2-1.png" style="display: block; margin: auto;" />
]

---

# Geom vs. Stat

.pull-left[

```r
ggplot(mpg, aes(displ, hwy)) +
* geom_smooth(stat="smooth")
```

<img src="ch2_files/figure-html/stat-smooth-1-1.png" style="display: block; margin: auto;" />
]
.pull-right[

```r
ggplot(mpg, aes(displ, hwy)) +
* stat_smooth(geom="smooth")
```

<img src="ch2_files/figure-html/stat-smooth-2-1.png" style="display: block; margin: auto;" />
]

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# Scales and Guides

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# Scale Specification

A **scale** is a procedure that performs the mapping of data attributes into channels (position, color, size...):

- sets the **limits**;

- sets an optional **transformation** (without modifying the data);

- sets a **guide**.

.pull-left[
A **guide** allows us to revert the procedure and recover the data:

- an axis or a legend, depending on the channel;

- has a name, breaks, labels...
]
.pull-right[
.center[![:scale 100%](assets/img/ch2/scale-guides.png)]
]

---

# Scale Specification

.font150[
Naming: `scale_<aes>_<type>(<arguments>)`
]

![:vspace 40]()

.font120[
| Element | Argument | Shortcut function |
|--------:|:---------|:------------------|
| Title   | `name=...`   | `labs(x=..., y=..., color=..., ...)` |
| Limits  | `limits=...` | `lims(x=..., y=..., color=..., ...)` |
| Breaks  | `breaks=...` | |
| Labels  | `labels=...` | |
| Guide   | `guide=...`  | `guides(x=..., y=..., color=..., ...)` |
| Transformation | `trans=...` | |
]

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# Tutorial 02
## [Scales and Guides](../tutorials/02/)

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# Coordinate Systems

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# Cartesian Coordinates

![:vspace 30]()

`coord_cartesian()`: default, no need to be specified

- ... although it is useful to set axes limits (via `xlim` and `ylim` arguments).

- Position given by orthogonal distances, `x` and `y`, to an origin.

Some helper functions:

- `coord_flip()`: helper to flip the axes.

- `coord_fixed()`: helper to fix the aspect ratio.

- `coord_trans()`: helper to transform the axes.

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# Other Coordinates

![:vspace 100]()

- `coord_polar()`: `x` is the angle, `y` is the radius (can be reverted).

- `coord_map()`: projections of the sphere into a plane.
  - Mercator, sinusoidal, cylindrical, rectangular...
  - Anything supported by the `mapproj` package.

- `coord_sf()`: modern way to deal with maps via **simple features** 
 (from `sf` package).

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# Tutorial 03
## [Coordinate Systems](../tutorials/03/)

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# Faceting

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# Facet Specification

![:vspace 50]()

.center[![:scale 80%](assets/img/ch2/position-facets.png)]

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# Facet Specification

.pull-left[
<img src="ch2_files/figure-html/facet-grid-1.png" style="display: block; margin: auto;" />
]
.pull-right[
<img src="ch2_files/figure-html/facet-wrap-1.png" style="display: block; margin: auto;" />
]

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# Tutorial 04
## [Faceting](../tutorials/04/)

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# Themes

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# Theme Specification

.footnote[Source: [ggplot2 Theme Elements Demonstration](https://henrywang.nl/ggplot2-theme-elements-demonstration/) by Henry Wang]

.center[![:scale 90%](assets/img/ch2/theme-elements.png)]

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# Tutorial 05
## [Themes](../tutorials/05/)

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# Annotations

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# Types of Annotations

.pull-left[

]
.pull-right[
<img src="ch2_files/figure-html/annotations0-1.png" style="display: block; margin: auto;" />
]

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# Types of Annotations

.pull-left[
- Guides (axes and legend)
]
.pull-right[
<img src="ch2_files/figure-html/annotations1-1.png" style="display: block; margin: auto;" />
]

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# Types of Annotations

.pull-left[
- Guides (axes and legend)

- Titles (title, subtitle and caption)
]
.pull-right[
<img src="ch2_files/figure-html/annotations2-1.png" style="display: block; margin: auto;" />
]

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# Types of Annotations

.pull-left[
- Guides (axes and legend)

- Titles (title, subtitle and caption)

- Text labels
]
.pull-right[
<img src="ch2_files/figure-html/annotations3-1.png" style="display: block; margin: auto;" />
]

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# Types of Annotations

.pull-left[
- Guides (axes and legend)

- Titles (title, subtitle and caption)

- Text labels

- Reference lines
]
.pull-right[
<img src="ch2_files/figure-html/annotations4-1.png" style="display: block; margin: auto;" />
]

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# Types of Annotations

.pull-left[
- Guides (axes and legend)

- Titles (title, subtitle and caption)

- Text labels

- Reference lines

- Reference areas
]
.pull-right[
<img src="ch2_files/figure-html/annotations5-1.png" style="display: block; margin: auto;" />
]

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# Types of Annotations

.pull-left[
- Guides (axes and legend)

- Titles (title, subtitle and caption)

- Text labels

- Reference lines

- Reference areas

- Direct labeling
]
.pull-right[
<img src="ch2_files/figure-html/annotations6-1.png" style="display: block; margin: auto;" />
]

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# Tutorial 06
## [Annotations](../tutorials/06/)

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# Arranging Plots

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# Types of Arrangements

.pull-left[
- Compositions

<img src="ch2_files/figure-html/compositions-1.png" style="display: block; margin: auto;" />
]
.pull-right[
- Insets

<img src="ch2_files/figure-html/insets-1.png" style="display: block; margin: auto;" />
]

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# Panel Alignment

.pull-left[
- None

<img src="ch2_files/figure-html/alignment-none-1.png" style="display: block; margin: auto;" /><img src="ch2_files/figure-html/alignment-none-2.png" style="display: block; margin: auto;" />
]
.pull-right[
- With [`patchwork`](https://patchwork.data-imaginist.com/)

<img src="ch2_files/figure-html/alignment-patchwork-1.png" style="display: block; margin: auto;" />
]

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# Tutorial 07
## [Arranging Plots](../tutorials/07/)