---
title: "Introduction to 'treemapify'"
author: "David Wilkins"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Introduction to 'treemapify'}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteDepends{ggplot2}
---

## The G20 dataset

'treemapify' includes an example dataset containing statistics about the G-20
group of major world economies.

```{r message = FALSE}
library(ggplot2)
library(treemapify)
G20
```

## Drawing a simple treemap

In a treemap, each tile represents a single observation, with the area of the
tile proportional to a variable. Let's start by drawing a treemap with each
tile representing a G-20 country. The area of the tile will be mapped to the
country's GDP, and the tile's fill colour mapped to its HDI (Human Development
Index). `geom_treemap()` is the basic geom for this purpose.

```{r basic_treemap}
ggplot(G20, aes(area = gdp_mil_usd, fill = hdi)) +
  geom_treemap()
```

This plot isn't very useful without the knowing what country is represented by
each tile. `geom_treemap_text()` can be used to add a text label to each tile. It
uses the ['ggfittext'](https://github.com/wilkox/ggfittext) package to resize
the text so it fits the tile. In addition to standard text formatting aesthetics
you would use in `geom_text()`, like `fontface` or `colour`, we can pass
additional options specific for 'ggfittext'. For example, we can place the text
in the centre of the tile with `place = "centre"`, and expand it to fill as much
of the tile as possible with `grow = TRUE`.

```{r geom_treemap_text}
ggplot(G20, aes(area = gdp_mil_usd, fill = hdi, label = country)) +
  geom_treemap() +
  geom_treemap_text(fontface = "italic", colour = "white", place = "centre",
                    grow = TRUE)
```

Note that several tiles in the top right corner have no labels.
`geom_treemap_text()` will hide text labels that cannot fit a tile without
being shrunk below a minimum size, by default 4 points. This can be adjusted
with the `min.size` argument.

## Subgrouping tiles

`geom_treemap()` supports subgrouping of tiles within a treemap by passing a
`subgroup` aesthetic. Let's subgroup the countries by region, draw a border
around each subgroup with `geom_treemap_subgroup_border()`, and label each
subgroup with `geom_treemap_subgroup_text()`. `geom_treemap_subgroup_text()`
takes the same arguments for text placement and resizing as
`geom_treemap_text()`.

```{r subgrouped_treemap}
ggplot(G20, aes(area = gdp_mil_usd, fill = hdi, label = country,
                subgroup = region)) +
  geom_treemap() +
  geom_treemap_subgroup_border() +
  geom_treemap_subgroup_text(place = "centre", grow = T, alpha = 0.5, colour =
                             "black", fontface = "italic", min.size = 0) +
  geom_treemap_text(colour = "white", place = "topleft", reflow = T)
```

Up to three nested levels of subgrouping are supported with the `subgroup2` and
`subgroup3` aesthetics. Borders and text labels for these subgroups can be
drawn with `geom_treemap_subgroup2_border()`, etc. Note that 'ggplot2' draws
plot layers in the order that they are added. This means it is possible to
accidentally hide one layer of subgroup borders with another. Usually, it's
best to add the border layers in order from deepest to shallowest, i.e.
`geom_treemap_subgroup3_border()` then `geom_treemap_subgroup2_border()` then
`geom_treemap_subgroup_border()`.

```{r many_subgroups}
ggplot(G20, aes(area = 1, label = country, subgroup = hemisphere,
                subgroup2 = region, subgroup3 = econ_classification)) +
  geom_treemap() +
  geom_treemap_subgroup3_border(colour = "blue", size = 1) +
  geom_treemap_subgroup2_border(colour = "white", size = 3) +
  geom_treemap_subgroup_border(colour = "red", size = 5) +
  geom_treemap_subgroup_text(
    place = "middle",
    colour = "red",
    alpha = 0.5,
    grow = T
  ) +
  geom_treemap_subgroup2_text(
    colour = "white",
    alpha = 0.5,
    fontface = "italic"
  ) +
  geom_treemap_subgroup3_text(place = "top", colour = "blue", alpha = 0.5) +
  geom_treemap_text(colour = "white", place = "middle", reflow = T)
```

As demonstrated, there is no assurance that the resulting plot will look good.

Like any 'ggplot2' plot, 'treemapify' plots can be faceted, scaled, themed, etc.

## Fixed layouts

The default algorithm for laying out the tiles is the 'squarified' algorithm.
This tries to minimise the tiles' aspect ratios, making sure there are no long
and flat or tall and skinny tiles. While 'squarified' treemaps are aesthetically
pleasing, the downside is that the position of tiles within the plot area can
change dramatically with even small changes to the dataset. This makes it
difficult to compare treemaps side-by-side, or create animated treemaps.

By providing the `layout = "fixed"` option to 'treemapify' geoms, an alternative
layout algorithm is used that will always position the tiles based on the order
of observations in the data frame. It's very important that the same value for
`layout` is passed to all 'treemapify' geoms, otherwise different layers of the
plot might not share the same layout.
