treemapify() returns a data frame of tile coordinates for a treemap layout of a set of observations. This is only useful if you wish to draw the treemap without the help of the ggplot2 geoms, or for some edge cases such as creating interactive treemaps with 'R Shiny' (see e.g. https://stackoverflow.com/q/45021775). The easiest way to draw a treemap with the 'treemapify' package is to use the provided 'ggplot2' geoms, such as geom_treemap().

data must be a tidy data frame, i.e. each row must represent a single observation and each column a single variable. You must provide the name of the variable that will be represented by the area of each treemap tile with area. Optionally, you can also select up to three variables (with subgroup, subgroup2 and subgroup3) to generate a layout in which the tiles are clustered into subgroups nested up to three levels deep.

Four layout algorithms are provided. With the default 'squarified' algorithm (layout = "squarified"), the priority is ensuring the tiles have an aesthetically pleasing aspect ratio; that is, they are not too narrow or too short. In this algorithm, tile placement proceeds from one corner, placing the tiles in either rows or columns until all the tiles are placed. See Bruls et al. (1999) for the full algorithm.

There are two variants on the 'squarified' algorithm. 'scol' forces tile placement to begin with a column, regardless of the effect on aspect ratio; 'srow' forces tile placement to been with a row. This will also apply to all subgroups. After the first row or column, the remaining tiles will be placed so as to optimise aspect ratios, as with the default algorithm.

With the 'fixed' layout algorithm (layout = "fixed"), the plot area is divided into vertical columns, which are each filled with an equal number of tiles beginning at the starting corner. Unlike the 'squarified' algorithm, with the 'fixed' algorithm the relative positions of the tiles are fixed by their order in the input data frame. This can result in aesthetically unpleasing layouts, but it allows side-by-side comparisons or animations to be created.

treemapify_fixed is an alias for treemapify(layout = "fixed").

treemapify(
data,
area,
subgroup,
subgroup2,
subgroup3,
layout = "squarified",
start = "bottomleft",
fill = NULL,
label = NULL,
group = NULL,
fixed = NULL,
xlim = c(0, 1),
ylim = c(0, 1)
)

treemapify_fixed(...)

## Arguments

data A tidy data frame. Name of the variable (a column in data) to be mapped to the area of treemap tiles. Optionally, names of variables (columns in data) by which the tiles should be grouped, at up to three nested levels. The layout algorithm, one of either 'squarified' (the default), 'scol', 'srow' or 'fixed'. See Details for full details on the different layout algorithms. The corner in which to start placing the tiles. One of 'bottomleft' (the default), 'topleft', 'topright' or 'bottomright'. Deprecated. Will be removed in later versions. Deprecated. Use subgroup instead. Will be removed in later versions. Deprecated. Use layout = "fixed" instead. Will be removed in later versions. The boundaries of the treemap in the x and y dimensions. Must be a numeric vector of length two; both default to c(0, 1). Additional arguments to be passed to treemapify().

## Details

treemapify is for generating a data frame of raw treemap coordinates. If you want to draw a treemap with 'ggplot2', use geom_treemap() instead.

## References

Bruls, M., Huizing, K., & van Wijk, J. (1999). Squarified Treemaps (pp. 33-42).Proceedings of the Joint Eurographics and IEEE TCVG Symposium on Visualization. http://www.win.tue.nl/~vanwijk/stm.pdf

geom_treemap()

## Examples


treemapify(G20, area = "gdp_mil_usd")
#>           region        country   hdi econ_classification hemisphere      ymax
#> 14        Europe European Union 0.876            Advanced   Northern 0.5113668
#> 2  North America  United States 0.937            Advanced   Northern 1.0000000
#> 7           Asia          China 0.699          Developing   Northern 0.3561040
#> 8           Asia          Japan 0.912            Advanced   Northern 0.3561040
#> 15        Europe        Germany 0.920            Advanced   Northern 0.5681398
#> 16        Europe         France 0.893            Advanced   Northern 0.5681398
#> 17        Europe United Kingdom 0.875            Advanced   Northern 0.5681398
#> 5  South America         Brazil 0.730          Developing   Southern 0.7290108
#> 12       Eurasia         Russia 0.788          Developing   Northern 0.8647700
#> 18        Europe          Italy 0.881            Advanced   Northern 1.0000000
#> 10          Asia          India 0.554          Developing   Northern 0.7141474
#> 20       Oceania      Australia 0.938            Advanced   Southern 0.8762440
#> 4  North America         Mexico 0.775          Developing   Northern 1.0000000
#> 9           Asia    South Korea 0.909            Advanced   Northern 0.8458414
#> 11          Asia      Indonesia 0.629          Developing   Southern 0.8458414
#> 13       Eurasia         Turkey 0.722          Developing   Northern 0.9263225
#> 19   Middle East   Saudi Arabia 0.782          Developing   Northern 1.0000000
#> 6  South America      Argentina 0.811          Developing   Southern 0.9310513
#> 1         Africa   South Africa 0.629          Developing   Southern 1.0000000
#>         ymin      xmin      xmax
#> 14 0.0000000 0.0000000 0.4461327
#> 2  0.5113668 0.0000000 0.4461327
#> 7  0.0000000 0.4461327 0.7672295
#> 8  0.0000000 0.7672295 1.0000000
#> 15 0.3561040 0.4461327 0.6690342
#> 16 0.3561040 0.6690342 0.8400295
#> 17 0.3561040 0.8400295 1.0000000
#> 5  0.5681398 0.4461327 0.6531338
#> 12 0.7290108 0.4461327 0.6531338
#> 18 0.8647700 0.4461327 0.6531338
#> 10 0.5681398 0.6531338 0.8268406
#> 3  0.5681398 0.8268406 1.0000000
#> 20 0.7141474 0.6531338 0.7853311
#> 4  0.8762440 0.6531338 0.7853311
#> 9  0.7141474 0.7853311 0.9073179
#> 11 0.7141474 0.9073179 1.0000000
#> 13 0.8458414 0.7853311 0.9225305
#> 19 0.9263225 0.7853311 0.9225305
#> 6  0.8458414 0.9225305 1.0000000
#> 1  0.9310513 0.9225305 1.0000000