Matplotlib Stacked Bar Chart

Introduction

In this lab, we will learn how to create a stacked bar chart using the Matplotlib library in Python. We will use penguin data to create a stacked bar chart that shows the number of penguins with above average body mass.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

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Import Libraries

We will start by importing the necessary libraries, including numpy and matplotlib.pyplot.

import matplotlib.pyplot as plt
import numpy as np

Define Data

We will define the data that we will use to create the stacked bar chart.

species = (
    "Adelie\n $\\mu=$3700.66g",
    "Chinstrap\n $\\mu=$3733.09g",
    "Gentoo\n $\\mu=5076.02g$",
)
weight_counts = {
    "Below": np.array([70, 31, 58]),
    "Above": np.array([82, 37, 66]),
}
width = 0.5

Create a Stacked Bar Chart

We will create a stacked bar chart using matplotlib.pyplot.bar and loop through each weight category to stack the bars.

fig, ax = plt.subplots()
bottom = np.zeros(3)

for boolean, weight_count in weight_counts.items():
    p = ax.bar(species, weight_count, width, label=boolean, bottom=bottom)
    bottom += weight_count

ax.set_title("Number of penguins with above average body mass")
ax.legend(loc="upper right")

Display the Chart

We will display the stacked bar chart using matplotlib.pyplot.show().

plt.show()

Summary

In this lab, we learned how to create a stacked bar chart using the Matplotlib library in Python. We started by importing the necessary libraries, defined the data that we will use to create the chart, and then created a stacked bar chart using matplotlib.pyplot.bar. Finally, we displayed the chart using matplotlib.pyplot.show().