How to create a bubble chart using plotly in R?
This recipe helps you create a bubble chart using plotly in R
Recipe Objective
Bubble plot is a type of scatter plot which not only uses cartesian coordinates to display the relation between two variables but also considers a third numerical variable represented by the size of the dots. Hence, we need three numerical variables, 2 for the x and y axis and 1 for the size of the dot.
In this recipe we are going to use Plotly package to plot the required bubble plot. Plotly package provides an interface to the plotly javascript library allowing us to create interactive web-based graphics entrirely in R. Plots created by plotly works in multiple format such as:
- R Markdown Documents
- Shiny apps - deploying on the web
- Windows viewer
Plotly has been actively developed and supported by it's community.
This recipe demonstrates how to plot a bubble plot in R using plotly package.
STEP 1: Loading required library and dataset
Dataset description: It is the basic data about the customers going to the supermarket mall. The variable that we are interested in: Annual.Income (which is in 1000s), Spending Score and age
# Data manipulation package
library(dplyr)
library(tidyverse)
# reading a dataset
customer_seg = read.csv('R_129_Mall_Customers.csv')
# selecting the required variables using the select() function
customer_seg_var = select(customer_seg, Age, Annual.Income..k..,Spending.Score..1.100.)
# summary of the selected variables
glimpse(customer_seg_var)
Observations: 200 Variables: 3 $ Age19, 21, 20, 23, 31, 22, 35, 23, 64, 30, 67, 35… $ Annual.Income..k.. 15, 15, 16, 16, 17, 17, 18, 18, 19, 19, 19, 19… $ Spending.Score..1.100. 39, 81, 6, 77, 40, 76, 6, 94, 3, 72, 14, 99, 1…
STEP 2: Plotting a bubble plot using Plotly
We use the plot_ly() function to plot a bubble plot between annual income and spending score variables using Age as a dot size
Syntax: plot_ly( data = , x = , y = , type = "scatter", mode = "markers", marker = list(size = , opacity = ))
Where:
- x = variable to be plotted in x axis
- y = variable to be plotted in y axis
- data = dataframe to be used
- type = type of the chart
- mode = This is the most important arguement for a bubble plot which indicates the mode to be of marker type in our case.
- marker = provides us with the size and opacity input to the graph
Note:
- The %>% sign in the syntax earlier makes the code more readable and enables R to read further code without breaking it.
- We also use layout() function to give a title to the graph
fig <- plot_ly(x = ~Annual.Income..k..[1:20], y = ~Spending.Score..1.100.[1:20],
data = customer_seg,
type = "scatter",
mode = "markers",
marker = list(size = ~Age, opacity = 0.5)) %>% layout(title = 'Bubble Plot using Plotly')
embed_notebook(fig)
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