LineUp is an interactive technique designed to create, visualize and explore rankings of items based on a set of heterogeneous attributes. This is a HTMLWidget wrapper around the JavaScript library LineUp.js. Details about the LineUp visualization technique can be found at https://jku-vds-lab.at/tools/lineup/.
It can be used within standalone R Shiny apps or R Markdown files. Crosstalk is supported for synching selections and filtering among widgets.
install.packages('lineupjs')
library(lineupjs)
lineup(mtcars)
lineup(iris)
lineup(iris,
ranking=lineupRanking(columns=c('_*', '*', 'impose'),
sortBy=c('Sepal_Length:desc'), groupBy=c('Species'),
impose=list(type='impose', column='Sepal_Length', categoricalColumn='Species')))
::install_github("jcheng5/d3scatter")
devtoolslibrary(d3scatter)
library(crosstalk)
= SharedData$new(iris)
shared_iris
d3scatter(shared_iris, ~Petal.Length, ~Petal.Width, ~Species, width="100%")
lineup(shared_iris, width="100%")
library(shiny)
library(crosstalk)
library(lineupjs)
library(d3scatter)
# Define UI for application that draws a histogram
<- fluidPage(
ui titlePanel("LineUp Shiny Example"),
fluidRow(
column(5, d3scatterOutput("scatter1")),
column(7, lineupOutput("lineup1"))
)
)
# Define server logic required to draw a histogram
<- function(input, output) {
server <- SharedData$new(iris)
shared_iris
$scatter1 <- renderD3scatter({
outputd3scatter(shared_iris, ~Petal.Length, ~Petal.Width, ~Species, width = "100%")
})
$lineup1 <- renderLineup({
outputlineup(shared_iris, width = "100%")
})
}
# Run the application
shinyApp(ui = ui, server = server)
Hint:
In case you see scrollbars in each cell it is because of the font the cells are too narrow, you can specify a larger row height using
lineup(iris, options=list(rowHeight=20))