Introduction to Bubble Plot in Python [Quick Guide]

A bubble plot is a variation of a scatter chart in which bubbles represent the data points of the data, and an additional dimension of the data represents the size of the points.

Also read: Python Plotly Tutorial

Advantages and Disadvantages of Bubble Chart

Just like the scatter, a bubble chart helps to depict and show relationships between various numeric values. However, the addition of marker size (the size of the bubble ) as a dimension allows us to compare three different variables at the same time!

Along with this, it displays data in 3-D which widens the scope of the analysis for the dataset. You can also add a fourth variable to add various colors to the plot.

The only disadvantage of the chart is that at times due to bubble sizes, the chart can get difficult to read and understand. As a result, it can’t be used to display tones of data.

Code Implementation of Bubble Plot

To create a bubble chart, we need a data table containing three different columns. Where two columns will correspond with the horizontal and vertical values of the plot ( the x and y-axis ) and the third will indicate the size of the points.

Importing the Modules

We will start off by loading the Pandas, NumPy and Matplotlib libraries using the code below.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

Creating Dataset for Bubble Plot

We will create the x and y variable values. Along with this, we will also create a third variable for the size of bubbles and a fourth variable to add colors to the plot.

x = np.random.normal(170, 20, 100) # 100 points for Normal Distribution
y = x + np.random.normal(5, 25, 100) # Generate y values for x values generated
colors = np.random.rand(100) # Colors as the third variable
area = (25 * np.random.rand(100))**2 # Size of Bubbles as fourth variable

We will store the data of the previous step in a Pandas dataframe using the code below.

data = pd.DataFrame({
    'X': x,
    'Y': y,
    'Colors': colors,
    "bubble_size":area})
data.head()

Create a simple Scatter Plot

We will start by making a simple scatter plot with the scatter function. We can customize the plot according to our own preferences but for now, look at the code below.

plt.scatter('X', 'Y', data=data)
plt.xlabel("X values", size=16)
plt.ylabel("Y values", size=16)
plt.title("A Simple Scatter Plot", size=18)
plt.show()

Creating Bubble Plot

We can make a bubble plot in Python using the same scatter function where we also need to specify size argument to define the size of the data points.

plt.scatter('X', 'Y', 
             s='bubble_size',
             alpha=0.5, 
             data=data)
plt.xlabel("X values", size=16)
plt.ylabel("Y values", size=16)
plt.title("A Simple Bubble Plot", size=18)
plt.show()

Add Colors to the Plot

To make visualizations better, we will add color to the bubbles using another variable in the plot.

plt.scatter('X', 'Y', 
             s='bubble_size',
            c='Colors',
             alpha=0.5, 
             data=data)
plt.xlabel("X values", size=16)
plt.ylabel("Y values", size=16)
plt.title("A Simple Bubble Plot", size=18)
plt.show()

Conclusion

Bubble charts are without a doubt one of the most useful charts when you wish to display complex variables. I hope you are now clear with what Bubble Plots are and how to implement the same using the Python programming language.

Thank you for reading!