When it comes to a ggplotly graph, it's easy to display informations when hovering over specific point. This code do the job :
toy_df=data.frame("t"=c(seq(1,10),seq(1,10)),
"value"=c(runif(10,0,10),2*runif(10,0,10)),
"event"=c(rep("A",10),rep("B",10)))
p <- ggplot() + geom_area(aes(y = value, x = t, fill=event), data = toy_df)
ggplotly(p)
But I would like to display informations when hovering over one of the area. Because in my case, area is an event that I want to be able to describe deeply.
Polygons in ggplot2
(geom_polygon
) provide a possible solutions.
Below you can find a rather raw code that should clarify the main idea:
library(ggplot2)
library(plotly)
set.seed(1)
toy_df=data.frame("t"=c(seq(1,10),seq(1,10)),
"value"=c(runif(10,0,10),2*runif(10,0,10)),
"event"=c(rep("A",10),rep("B",10)))
# In order to create polygons like in geom_areas,
# two points on the x-axis must be added: one at t=1 and one at t=10
toy_df2 <- toy_df[NULL,]
for (k in unique(toy_df$event)) {
subdf <- subset(toy_df, toy_df$event==k)
nr <- nrow(subdf)
row1 <- subdf[1,]
row1$value <- 0
row2 <- subdf[nr,]
row2$value <- 0
toy_df2 <- rbind(toy_df2, row1, subdf, row2)
}
# Stack polygons
toy_df2$value[toy_df2$event=="A"] <- toy_df2$value[toy_df2$event=="A"] +
toy_df2$value[toy_df2$event=="B"]
# Calculate mean values for the two events: they will be displayed in the tooltip
toy_df2 <- toy_df2 %>% group_by(event) %>% mutate(mn=round(mean(value),3))
p <- ggplot(data = toy_df2, aes(y = value, x = t, fill=event,
text=paste0("Value:", mn,"<br>Event:", event))) +
geom_polygon()
ggplotly(p, tooltip="text")