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uRosConf/voronoiTreemap
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This is the development place for R-package voronoiTreemap
- A side event to the annual conferenceThe Use of R in Official Statistics
- https://github.com/uRosConf/unconfUROS2018
- Make it easy to create a plot like this:
knitr::include_graphics("documentation/preisKalei.jpg")
- https://github.com/uRosConf/voronoiTreemap
- important functions:
- vt_input_from_df ... easy data input as a data frame
- vt_export_json ... export to json
- vt_d3 ... create an htmlwidget
- vt_app ... start a shiny to create a Voronoi treemap
library(voronoiTreemap)data(ExampleGDP)knitr::kable(head(ExampleGDP,3))
| h1 | h2 | h3 | color | weight | codes |
|---|---|---|---|---|---|
| Total | Asia | China | #f58321 | 14.84 | CN |
| Total | Asia | Japan | #f58321 | 5.91 | JP |
| Total | Asia | India | #f58321 | 2.83 | IN |
gdp_json<- vt_export_json(vt_input_from_df(ExampleGDP))vt_d3(gdp_json)
vt_d3(gdp_json,label=FALSE,color_border="#000000",size_border="2px",legend=TRUE)
- You can set a seed (in Javascript)!
vt_d3(gdp_json,legend=TRUE,legend_title="Continents",seed=1)
- Colors can be provided for each cell independently.
data(canada)canada<-canada[canada$h1=="Canada",]canada$codes<-canada$h3canadaH<- vt_export_json(vt_input_from_df(canada,scaleToPerc=FALSE))vt_d3(canadaH,label=FALSE,width=400,height=400)
- Colors could be computed according to a numeric variable, e.g. with thescales package.
canada$color<-scales::seq_gradient_pal(low="#999999",high="#ffffff")(canada$weight/max(canada$weight))canadaH<- vt_export_json(vt_input_from_df(canada,scaleToPerc=FALSE))vt_d3(canadaH,label=FALSE,width=400,height=400,color_border="#000000")
knitr::include_graphics("documentation/shiny1.jpg")
knitr::include_graphics("documentation/shiny2.jpg")
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R package for voronoi treemaps with added interactivity by shiny
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