in reply to this tweet
Anyone made interactive (tooltips, zoomable, etc.) plots of CART analyses in R? @timelyportfolio @yaacovp @xieyihui @ramnath_vaidya?
— Andrew Menzel (@menzbasketball) September 3, 2014I put a quick rCharts example together forking this fine collapsible d3 tree with pan/zoom.
I have included the code for this particular example in this gist. Also this rCharts_rpart repo contains some experiments and the pieces needed for rCharts.
library(rpart)
library(partykit)
library(rCharts)
library(jsonlite)
#set up a little rpart as an example
rp <- rpart(
hp ~ cyl + disp + mpg + drat + wt + qsec + vs + am + gear + carb,
method = "anova",
data = mtcars,
control = rpart.control(minsplit = 4)
)
#convert it to partykit rpart so we can use structure
rpk <- as.party(rp)
#set up rCharts
#key is to define how to handle the data
rChartsRpart <- setRefClass(
"rChartsRpart",
contains = "Dimple",
methods = list(
initialize = function(){
callSuper();
},
getPayload = function (chartId) {
data = jsonlite::toJSON(
rapply(params$data$node,unclass,how="replace")
,auto_unbox = T
)
data = gsub( x=data, pattern = "kids", replacement="children")
data = gsub ( x=data, pattern = '"id":([0-9]*)', replacement = '"name":"node\\1"' )
chart = toChain(params$chart, "myChart")
controls_json = toJSON(params$controls)
controls = setNames(params$controls, NULL)
opts = toJSON2(params[!(names(params) %in% c("data", "chart",
"controls"))])
list(opts = opts, data = data, chart = chart, chartId = chartId,
controls = controls, controls_json = controls_json)
}
)
)
# now make a rChart with our rpart
rpRc <- rChartsRpart$new()
rpRc$setLib("http://timelyportfolio.github.io/rCharts_rpart")
rpRc$lib = "rpart_tree"
rpRc$LIB$name = "rpart_tree"
rpRc$setTemplate(
chartDiv = "<{{container}} id = '{{ chartId }}' class = '{{ lib }}' style = 'height:100%;width:100%;'></{{ container}}>"
)
rpRc$set(
data = rpk
, height = 800
, width = 800
)
rpRc