I am trying to create a boxplot with ggplot and plotly with the dataset airquality
where Month
is on the x-axis and Ozone
values are o
I found solution on https://github.com/ropensci/plotly/issues/887
Try to make this kind of code !
library(plotly)
vals <- boxplot(airquality$Ozone,plot = FALSE)
y <- airquality[airquality$Ozone > vals$stats[5,1] | airquality$Ozone < vals$stats[1,1],]
plot_ly(airquality,y = ~Ozone,x = ~Month,type = "box") %>%
add_markers(data = y, text = y$Day)
We can almost get it like this:
library(ggplot2)
library(plotly)
library(datasets)
data(airquality)
# add months
airquality$Month <- factor(airquality$Month,
labels = c("May", "Jun", "Jul", "Aug", "Sep"))
# add sample names
airquality$Sample <- paste0('Sample_',seq(1:nrow(airquality)))
# boxplot
gg <- ggplot(airquality, aes(x = Month, y = Ozone)) +
geom_boxplot()
ggly <- ggplotly(gg)
# add hover info
hoverinfo <- with(airquality, paste0("sample: ", Sample, "</br></br>",
"month: ", Month, "</br>",
"ozone: ", Ozone))
ggly$x$data[[1]]$text <- hoverinfo
ggly$x$data[[1]]$hoverinfo <- c("text", "boxes")
ggly
Unfortunately, the hovering does not work for the first box plot...
This method will achieve the same result but does not show the boxplot summary statistics hover. Removes outlier and hover on boxplot layer and overlays a geom_point layer of only outliers with hover info. The definition of outliers for plotly are stated here. This method would work better than other solutions when dealing with more complex graphs (e.g. grouped side by side boxplots). Interestingly, the ggplotly boxplot graph for this data is not the same as the ggplot graph. The upper fence whisker for Aug in ggplotly extends much further than the ggplot upper fence whisker for Aug.
library(dplyr)
library(plotly)
library(datasets)
library(ggplot2)
data(airquality)
# manipulate data
mydata = airquality %>%
# add months
mutate(Month = factor(airquality$Month,labels = c("May", "Jun", "Jul", "Aug", "Sep")),
# add sample names
Sample = paste0('Sample_',seq(1:n())))%>%
# label if outlier sample by Month
group_by(Month) %>%
mutate(OutlierFlag = ifelse((Ozone<quantile(Ozone,1/3,na.rm=T)-1.5*IQR(Ozone,na.rm=T)) | (Ozone>quantile(Ozone,2/3,na.rm=T)+1.5*IQR(Ozone,na.rm=T)),'Outlier','NotOutlier'))%>%
group_by()
# boxplot
p <- ggplot(mydata, aes(x = Month, y = Ozone)) +
geom_boxplot()+
geom_point(data=mydata %>% filter(OutlierFlag=="Outlier"),aes(group=Month,label1=Sample,label2=Ozone),size=2)
output = ggplotly(p, tooltip=c("label1","label2"))
# makes boxplot outliers invisible and hover info off
for (i in 1:length(output$x$data)){
if (output$x$data[[i]]$type=="box"){
output$x$data[[i]]$marker$opacity = 0
output$x$data[[i]]$hoverinfo = "none"
}
}
# print end result of plotly graph
output
I've managed to achieve this with Shiny.
library(plotly)
library(shiny)
library(htmlwidgets)
library(datasets)
# Prepare data ----
data(airquality)
# add months
airquality$Month <- factor(airquality$Month,
labels = c("May", "Jun", "Jul", "Aug", "Sep"))
# add sample names
airquality$Sample <- paste0('Sample_', seq(1:nrow(airquality)))
# Plotly on hover event ----
addHoverBehavior <- c(
"function(el, x){",
" el.on('plotly_hover', function(data) {",
" if(data.points.length==1){",
" $('.hovertext').hide();",
" Shiny.setInputValue('hovering', true);",
" var d = data.points[0];",
" Shiny.setInputValue('left_px', d.xaxis.d2p(d.x) + d.xaxis._offset);",
" Shiny.setInputValue('top_px', d.yaxis.l2p(d.y) + d.yaxis._offset);",
" Shiny.setInputValue('dx', d.x);",
" Shiny.setInputValue('dy', d.y);",
" Shiny.setInputValue('dtext', d.text);",
" }",
" });",
" el.on('plotly_unhover', function(data) {",
" Shiny.setInputValue('hovering', false);",
" });",
"}")
# Shiny app ----
ui <- fluidPage(
tags$head(
# style for the tooltip with an arrow (http://www.cssarrowplease.com/)
tags$style("
.arrow_box {
position: absolute;
pointer-events: none;
z-index: 100;
white-space: nowrap;
background: rgb(54,57,64);
color: white;
font-size: 14px;
border: 1px solid;
border-color: rgb(54,57,64);
border-radius: 1px;
}
.arrow_box:after, .arrow_box:before {
right: 100%;
top: 50%;
border: solid transparent;
content: ' ';
height: 0;
width: 0;
position: absolute;
pointer-events: none;
}
.arrow_box:after {
border-color: rgba(136, 183, 213, 0);
border-right-color: rgb(54,57,64);
border-width: 4px;
margin-top: -4px;
}
.arrow_box:before {
border-color: rgba(194, 225, 245, 0);
border-right-color: rgb(54,57,64);
border-width: 10px;
margin-top: -10px;
}")
),
div(
style = "position:relative",
plotlyOutput("myplot"),
uiOutput("hover_info")
)
)
server <- function(input, output){
output$myplot <- renderPlotly({
airquality[[".id"]] <- seq_len(nrow(airquality))
gg <- ggplot(airquality, aes(x=Month, y=Ozone, ids=.id)) + geom_boxplot()
ggly <- ggplotly(gg, tooltip = "y")
ids <- ggly$x$data[[1]]$ids
ggly$x$data[[1]]$text <-
with(airquality, paste0("<b> sample: </b>", Sample, "<br/>",
"<b> month: </b>", Month, "<br/>",
"<b> ozone: </b>", Ozone))[ids]
ggly %>% onRender(addHoverBehavior)
})
output$hover_info <- renderUI({
if(isTRUE(input[["hovering"]])){
style <- paste0("left: ", input[["left_px"]] + 4 + 5, "px;", # 4 = border-width after
"top: ", input[["top_px"]] - 24 - 2 - 1, "px;") # 24 = line-height/2 * number of lines; 2 = padding; 1 = border thickness
div(
class = "arrow_box", style = style,
p(HTML(input$dtext),
style="margin: 0; padding: 2px; line-height: 16px;")
)
}
})
}
shinyApp(ui = ui, server = server)