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🌳 Draw treemaps in ggplot2
wilkox/treemapify
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treemapify providesggplot2 geoms fordrawingtreemaps.
Install the release version of treemapify from CRAN:
install.packages("treemapify")
If you want the development version, install it from GitHub:
devtools::install_github("wilkox/treemapify")
treemapify includes an example dataset containing statistics about theG-20 group of major world economies.
library(ggplot2)library(treemapify)G20#> region country gdp_mil_usd hdi econ_classification#> 1 Africa South Africa 384315 0.629 Developing#> 2 North America United States 15684750 0.937 Advanced#> 3 North America Canada 1819081 0.911 Advanced#> 4 North America Mexico 1177116 0.775 Developing#> 5 South America Brazil 2395968 0.730 Developing#> 6 South America Argentina 474954 0.811 Developing#> 7 Asia China 8227037 0.699 Developing#> 8 Asia Japan 5963969 0.912 Advanced#> 9 Asia South Korea 1155872 0.909 Advanced#> 10 Asia India 1824832 0.554 Developing#> 11 Asia Indonesia 878198 0.629 Developing#> 12 Eurasia Russia 2021960 0.788 Developing#> 13 Eurasia Turkey 794468 0.722 Developing#> 14 Europe European Union 16414483 0.876 Advanced#> 15 Europe Germany 3400579 0.920 Advanced#> 16 Europe France 2608699 0.893 Advanced#> 17 Europe United Kingdom 2440505 0.875 Advanced#> 18 Europe Italy 2014079 0.881 Advanced#> 19 Middle East Saudi Arabia 727307 0.782 Developing#> 20 Oceania Australia 1541797 0.938 Advanced#> hemisphere#> 1 Southern#> 2 Northern#> 3 Northern#> 4 Northern#> 5 Southern#> 6 Southern#> 7 Northern#> 8 Northern#> 9 Northern#> 10 Northern#> 11 Southern#> 12 Northern#> 13 Northern#> 14 Northern#> 15 Northern#> 16 Northern#> 17 Northern#> 18 Northern#> 19 Northern#> 20 Southern
In a treemap, each tile represents a single observation, with the areaof the tile proportional to a variable. Let’s start by drawing a treemapwith each tile representing a G-20 country. The area of the tile will bemapped to the country’s GDP, and the tile’s fill colour mapped to itsHDI (Human Development Index).geom_treemap()
is the basic geom forthis purpose.
ggplot(G20, aes(area=gdp_mil_usd,fill=hdi))+ geom_treemap()
This plot isn’t very useful without the knowing what country isrepresented by each tile.geom_treemap_text()
can be used to add atext label to each tile. It uses theggfittext package to resize thetext so it fits the tile. In addition to standard text formattingaesthetics you would use ingeom_text()
, likefontface
orcolour
,we can pass additional options specific for ggfittext. For example, wecan place the text in the centre of the tile withplace = "centre"
,and expand it to fill as much of the tile as possible withgrow = TRUE
.
ggplot(G20, aes(area=gdp_mil_usd,fill=hdi,label=country))+ geom_treemap()+ geom_treemap_text(fontface="italic",colour="white",place="centre",grow=TRUE)
geom_treemap()
supports subgrouping of tiles within a treemap bypassing asubgroup
aesthetic. Let’s subgroup the countries by region,draw a border around each subgroup withgeom_treemap_subgroup_border()
, and label each subgroup withgeom_treemap_subgroup_text()
.geom_treemap_subgroup_text()
takes thesame arguments for text placement and resizing asgeom_treemap_text()
.
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)
Note that Argentina is not labelled.geom_treemap_text()
will hidetext labels that cannot fit a tile without being shrunk below a minimumsize, by default 4 points. This can be adjusted with themin.size
argument.
Up to three nested levels of subgrouping are supported with thesubgroup2
andsubgroup3
aesthetics. Borders and text labels forthese subgroups can be drawn withgeom_treemap_subgroup2_border()
,etc. Note that ggplot2 draws plot layers in the order that they areadded. This means it is possible to accidentally hide one layer ofsubgroup borders with another. Usually, it’s best to add the borderlayers in order from deepest to shallowest, i.e.geom_treemap_subgroup3_border()
thengeom_treemap_subgroup2_border()
thengeom_treemap_subgroup_border()
.
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 lookgood.
Like any ggplot2 plot, treemapify plots can be faceted, scaled, themed,etc.
ggplot(G20, aes(area=gdp_mil_usd,fill=region,label=country,subgroup=region))+ geom_treemap()+ geom_treemap_text(grow=T,reflow=T,colour="black")+ facet_wrap(~hemisphere)+ scale_fill_brewer(palette="Set1")+ theme(legend.position="bottom")+ labs(title="The G-20 major economies by hemisphere",caption="The area of each tile represents the country's GDP as a proportion of all countries in that hemisphere",fill="Region" )
The default algorithm for laying out the tiles is the ‘squarified’algorithm. This tries to minimise the tiles’ aspect ratios, making surethere are no long and flat or tall and skinny tiles. While ‘squarified’treemaps are aesthetically pleasing, the downside is that the positionof tiles within the plot area can change dramatically with even smallchanges to the dataset. This makes it difficult to compare treemapsside-by-side, or create animated treemaps.
By providing thelayout = "fixed"
option to treemapify geoms, analternative layout algorithm is used that will always position the tilesbased on the order of observations in the data frame. It’s veryimportant that the same value forlayout
is passed to all treemapifygeoms, otherwise different layers of the plot might not share the samelayout.
With the help oflayout = "fixed"
, and with thegganimate
package, itbecomes possible to create animated treemaps showing e.g. change overtime.
library(gganimate)library(gapminder)p<- ggplot(gapminder, aes(label=country,area=pop,subgroup=continent,fill=lifeExp ))+ geom_treemap(layout="fixed")+ geom_treemap_text(layout="fixed",place="centre",grow=TRUE,colour="white")+ geom_treemap_subgroup_text(layout="fixed",place="centre")+ geom_treemap_subgroup_border(layout="fixed")+ transition_time(year)+ ease_aes('linear')+ labs(title="Year: {frame_time}")anim_save("man/figures/animated_treemap.gif",p,nframes=48)