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geom_density2d in ggplot2

How to make a density map using geom_density2d.


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 2D Graph

Source: Brett Carpenter from Data.World

library(plotly)
beers <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/beers.csv", stringsAsFactors = FALSE)

p <- ggplot(beers, aes(x=abv, y=ibu)) +
  geom_density2d() +
  labs(y = "bitterness (IBU)",
       x = "alcohol volume (ABV)",
       title = "Craft beers from American breweries")

ggplotly(p)

Filled

Since each of the lines (in the above graph) shows a different "level", setting "fill = stat(level)" allows for a filled graph.

library(plotly)
beers <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/beers.csv", stringsAsFactors = FALSE)

p <- ggplot(beers, aes(x=abv, y=ibu)) +
  stat_density2d(aes(fill = stat(level)), geom="polygon") +
  labs(y = "bitterness (IBU)",
       x = "alcohol volume (ABV)",
       title = "Craft beers from American breweries")

ggplotly(p)

Preset Colourscale

"Viridis" colourscales are designed to still be perceptible in black-and-white, as well as for those with colourblindness. It comes with five colourscales, selected using the option= parameter: "magma" (or "A"), "inferno" (or "B"), "plasma" (or "C"), "viridis" (or "D", the default), and "cividis" (or "E").

library(plotly)
beers <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/beers.csv", stringsAsFactors = FALSE)

p <- ggplot(beers, aes(x=abv, y=ibu)) +
  stat_density2d(aes(fill = stat(level)), geom="polygon") +
  scale_fill_viridis_c(option = "plasma") +
  theme(legend.position = "magma") +
  labs(y = "bitterness (IBU)",
       x = "alcohol volume (ABV)",
       title = "Craft beers from American breweries")

ggplotly(p)

Customized Colourscale

You can also set your own colour gradients by defining a high and low point.

library(plotly)
beers <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/beers.csv", stringsAsFactors = FALSE)

p <- ggplot(beers, aes(x=abv, y=ibu)) +
  stat_density2d(aes(fill = stat(level)), geom="polygon") +
  scale_fill_gradient(low = "lightskyblue1", high = "darkred") +
  theme(legend.position = "none") +
  labs(y = "bitterness (IBU)",
       x = "alcohol volume (ABV)",
       title = "Craft beers from American breweries")

ggplotly(p)

Overlaid Points

I use variable "style2" to filter out the six most common beer styles. This way, we can see that the cluster of beers in the top right (i.e. more bitter and higher alcohol content) are IPAs - perhaps unsurprisingly.

library(plotly)
library(dplyr)
beers <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/beers.csv", stringsAsFactors = FALSE)

p <- ggplot(beers, aes(x=abv, y=ibu)) +
  geom_density2d(alpha=0.5) +
  geom_point(data=filter(beers, !is.na(style2)), aes(colour=style2, text = label), alpha=0.3) +
  labs(y = "bitterness (IBU)",
       x = "alcohol volume (ABV)",
       title = "Craft beers from American breweries",
       colour = "Beer types")

ggplotly(p)

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)