Visualizing categorical summaries
As you've learned in this chapter, Seaborn has many great visualizations for exploration, including a bar plot for displaying an aggregated average value by category of data.
In Seaborn, bar plots include a vertical bar indicating the 95% confidence interval for the categorical mean. Since confidence intervals are calculated using both the number of values and the variability of those values, they give a helpful indication of how much data can be relied upon.
Your task is to create a bar plot to visualize the means and confidence intervals of unemployment rates across the different continents.
unemployment is available, and the following have been imported for you: Seaborn as sns, matplotlib.pyplot as plt, and pandas as pd.
This exercise is part of the course
Exploratory Data Analysis in Python
Exercise instructions
- Create a bar plot showing continents on the x-axis and their respective average 2021 unemployment rates on the y-axis.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create a bar plot of continents and their average unemployment
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plt.show()