A **stacked bar chart **is a type of chart that uses bars to display the frequencies of different categories.

We can create this type of chart in Matplotlib by using the matplotlib.pyplot.bar() function.

This tutorial shows how to use this function in practice.

**Create a Basic Stacked Bar Chart**

The following code shows how to create a stacked bar chart to display the total sales of two products during four different sales quarters:

import numpy as np import matplotlib.pyplot as plt #create data quarter = ['Q1', 'Q2', 'Q3', 'Q4'] product_A = [14, 17, 12, 9] product_B = [7, 15, 24, 18] #define chart parameters N = 4 barWidth = .5 xloc = np.arange(N) #display stacked bar chart p1 = plt.bar(xloc, product_A, width=barWidth) p2 = plt.bar(xloc, product_B, bottom=product_A, width=barWidth) plt.show()

**Add a Title, Labels, and Legend**

We can also add a title, labels, tick marks, and a legend to make the chart easier to read:

import numpy as np import matplotlib.pyplot as plt #create data for two teams quarter = ['Q1', 'Q2', 'Q3', 'Q4'] product_A = [14, 17, 12, 9] product_B = [7, 15, 24, 18] #define chart parameters N = 4 barWidth = .5 xloc = np.arange(N) #create stacked bar chart p1 = plt.bar(xloc, product_A, width=barWidth) p2 = plt.bar(xloc, product_B, bottom=product_A, width=barWidth) #add labels, title, tick marks, and legend plt.ylabel('Sales') plt.xlabel('Quarter') plt.title('Sales by Product & Quarter') plt.xticks(xloc, ('Q1', 'Q2', 'Q3', 'Q4')) plt.yticks(np.arange(0, 41, 5)) plt.legend((p1[0], p2[0]), ('A', 'B')) #display chart plt.show()

**Customize Chart Colors**

Lastly, we can customize the colors used in the chart with the **colors() **argument within **plt.bar()**:

import numpy as np import matplotlib.pyplot as plt #create data for two teams quarter = ['Q1', 'Q2', 'Q3', 'Q4'] product_A = [14, 17, 12, 9] product_B = [7, 15, 24, 18] #define chart parameters N = 4 barWidth = .5 xloc = np.arange(N) #create stacked bar chart p1 = plt.bar(xloc, product_A, width=barWidth, color='springgreen') p2 = plt.bar(xloc, product_B, bottom=product_A, width=barWidth, color='coral') #add labels, title, tick marks, and legend plt.ylabel('Sales') plt.xlabel('Quarter') plt.title('Sales by Product & Quarter') plt.xticks(xloc, ('Q1', 'Q2', 'Q3', 'Q4')) plt.yticks(np.arange(0, 41, 5)) plt.legend((p1[0], p2[0]), ('A', 'B')) #display chart plt.show()

You can find a complete list of available colors within the Matplotlib documentation.

**Additional Resources**

The following tutorials explain how to perform other common tasks in Matplotlib:

How to Change Font Sizes on a Matplotlib Plot

How to Remove Ticks from Matplotlib Plots

How to Show Gridlines on Matplotlib Plots