Shapes in ggplot2

How to make Shapes in ggplot2 with Plotly.

New to Plotly?

Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Basic Ploygon

library(plotly)
library(ggplot2)

ids <- factor(c("1.1", "2.1", "1.2", "2.2", "1.3", "2.3"))

values <- data.frame(
  id = ids,
  value = c(3, 3.1, 3.1, 3.2, 3.15, 3.5)
)

positions <- data.frame(
  id = rep(ids, each = 4),
  x = c(2, 1, 1.1, 2.2, 1, 0, 0.3, 1.1, 2.2, 1.1, 1.2, 2.5, 1.1, 0.3,
  0.5, 1.2, 2.5, 1.2, 1.3, 2.7, 1.2, 0.5, 0.6, 1.3),
  y = c(-0.5, 0, 1, 0.5, 0, 0.5, 1.5, 1, 0.5, 1, 2.1, 1.7, 1, 1.5,
  2.2, 2.1, 1.7, 2.1, 3.2, 2.8, 2.1, 2.2, 3.3, 3.2)
)

datapoly <- merge(values, positions, by=c("id"))

p <- ggplot(datapoly, aes(x=x, y=y)) + geom_polygon(aes(fill=value, group=id))

ggplotly(p)

Ellipses

library(devtools)
library(ggplot2)
library(proto)

n <- 200
x1 <- rnorm(n, mean = 2)
y1 <- 1.5 + 0.4 * x1 + rnorm(n)
x2 <- rnorm(n, mean = -1)
y2 <- 3.5 - 1.2 * x2 + rnorm(n)
class <- rep(c("A", "B"), each = n)
df <- data.frame(x = c(x1, x2), y = c(y1, y2), colour = class)

p <- qplot(data = df, x = x, y = y, colour = class) +
  stat_ellipse(geom = "polygon", alpha = 1/2, aes(fill = class))

ggplotly(p)

Highlighting

library(plotly)
library(ggplot2)

tmp <-  with(mtcars, data.frame(x=c(0, 0, max(wt)*35), y=c(0, max(wt), max(wt))))

p <- ggplot(mtcars, aes(hp, wt)) +
  geom_polygon(data=tmp, aes(x, y), fill="#d8161688") +
  geom_point()

ggplotly(p)

Vertical Conversion

library(plotly)
library(ggplot2)

library(data.table)
df<-data.table(Product=letters[1:10], minX=1:10, maxX=5:14, minY= 10:1, maxY=14:5)

df.t<-data.table(rbind( df[,list(Product,X=minX,Y=minY)],
       df[,list(Product,X=minX,Y=maxY)],
       df[,list(Product,X=maxX,Y=minY)],
       df[,list(Product,X=maxX,Y=maxY)]))[
      order(Product,X,Y)]

p <- ggplot(df,aes(xmin=minX,xmax=maxX,ymin=minY,ymax=maxY,fill=Product))+
  geom_rect()

ggplotly(p)

Distributions

library(plotly)
library(ggplot2)

x=seq(-2,2,length=200)
dat <- data.frame(
  norm = dnorm(x,mean=0,sd=0.2),
  logistic = dlogis(x,location=0,scale=0.2), x = x
)
p <- ggplot(data=dat, aes(x=x)) +
  geom_polygon(aes(y=norm), fill="red", alpha=0.6) +
  geom_polygon(aes(y=logistic), fill="blue", alpha=0.6) +
  xlab("z") + ylab("") +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0))

ggplotly(p)

Convex Hull

library(plotly)
library(RColorBrewer)
library(ggplot2)

# Generate some data
nn <- 500
myData <- data.frame(X = rnorm(nn),
                     Y = rnorm(nn))

setK = 6  # How many clusters?
clusterSolution <- kmeans(myData, centers = setK)

myData$whichCluster <- factor(clusterSolution$cluster)

splitData <- split(myData, myData$whichCluster)
appliedData <- lapply(splitData, function(df){
  df[chull(df), ]  # chull really is useful, even outside of contrived examples.
  })
combinedData <- do.call(rbind, appliedData)

zp3 <- ggplot(data = myData,
                     aes(x = X, y = Y))
zp3 <- zp3 + geom_polygon(data = combinedData,  # This is also a nice example of how to plot
                          aes(x = X, y = Y, fill = whichCluster),  # two superimposed geoms
                          alpha = 1/2)                             # from different data.frames
zp3 <- zp3 + geom_point(size=1)
zp3 <- zp3 + coord_equal()
zp3 <- zp3 + scale_fill_manual(values = colorRampPalette(rev(brewer.pal(11, "Spectral")))(setK))

ggplotly(zp3)

What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at https://dashr.plot.ly/installation.

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:

library(plotly)

fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 

library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)

app <- Dash$new()
app$layout(
    htmlDiv(
        list(
            dccGraph(figure=fig) 
        )
     )
)

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)