The stacked plot owes its name to the fact that it represents the area under a line plot and that several such plots can be stacked on top of one another, giving the feeling of a stack. The stacked plot can be useful when we want to visualize the cumulative effect of multiple variables being plotted on the y axis.

In order to simplify this, think of an area plot as a line plot that shows the area covered by filling it with a color. Enough talk. Let's dive into the code base. First of all, let's define the dataset:

# House loan Mortgage cost per month for a year
houseLoanMortgage = [9000, 9000, 8000, 9000, 
                    8000, 9000, 9000, 9000, 
                    9000, 8000, 9000, 9000]

# Utilities Bills for a year
utilitiesBills = [4218, 4218, 4218, 4218,
                  4218, 4218, 4219, 2218, 
                  3218, 4233, 3000, 3000]
# Transportation bill for a year
transportation = [782, 900, 732, 892,
                  334, 222, 300, 800, 
                  900, 582, 596, 222]

# Car mortgage cost for one year
carMortgage = [700, 701, 702, 703, 
              704, 705, 706, 707, 
              708, 709, 710, 711]

Now, let's import the required libraries and plot stacked charts:

import matplotlib.pyplot as plt
import seaborn as sns
sns.set()

months= [x for x in range(1,13)]

# Create placeholders for plot and add required color 
plt.plot([],[], color='sandybrown', label='houseLoanMortgage')
plt.plot([],[], color='tan', label='utilitiesBills')
plt.plot([],[], color='bisque', label='transportation')
plt.plot([],[], color='darkcyan', label='carMortgage')

# Add stacks to the plot
plt.stackplot(months, houseLoanMortgage, utilitiesBills, transportation, carMortgage, colors=['sandybrown', 'tan', 'bisque', 'darkcyan'])
plt.legend()

# Add Labels
plt.title('Household Expenses')
plt.xlabel('Months of the year')
plt.ylabel('Cost')

# Display on the screen
plt.show()

In the preceding snippet, first, we imported matplotlib and seaborn. Nothing new, right? Then we added stacks with legends. Finally, we added labels to the axes and displayed the plot on the screen. Easy and straightforward. Now you know how to create an area plot or stacked plot. The area plot generated by the preceding code is as follows:

Now the most important part is the ability to interpret the graph. In the preceding graph, it is clear that the house mortgage loan is the largest expense since the area under the curve for the house mortgage loan is the largest. Secondly, the area of utility bills stack covers the second-largest area, and so on. The graph clearly disseminates meaningful information to the targeted audience. Labels, legends, and colors are important aspects of creating a meaningful visualization.