Python Boxplot Show Mean

Introduction

Boxplots are a useful visualization tool in data analysis. They provide a way to display the distribution of data based on quartiles, and can help identify outliers and skewness in the data. One attribute that can be added to a boxplot is the mean value of the data. In this article, we will explore how to create a boxplot in Python and how to display the mean value.

Creating a Boxplot in Python

There are several libraries available in Python for creating boxplots, but we will focus on the matplotlib library. Here's an example code snippet for creating a basic boxplot:

import matplotlib.pyplot as plt
import numpy as np

# Generate some random data
data = np.random.normal(size=(100,))

# Create a boxplot
plt.boxplot(data)

# Show the plot
plt.show()

This code generates a boxplot for a randomly generated set of data. The resulting plot should look something like this:

Adding Mean Value to Boxplot

To add the mean value to the boxplot, we can use the showmeans parameter of boxplot() function. Here's the updated code snippet:

import matplotlib.pyplot as plt
import numpy as np

# Generate some random data
data = np.random.normal(size=(100,))

# Create a boxplot with mean value displayed
plt.boxplot(data, showmeans=True)

# Show the plot
plt.show()

This code adds the showmeans=True parameter to the boxplot() function, which displays the mean value in the plot. The resulting plot should look something like this:

Conclusion

Boxplots are a powerful way to visualize data distributions, and adding the mean value to a boxplot can provide additional insights into the data. In this article, we explored how to create a basic boxplot using matplotlib, and how to add the mean value to the plot. With these tools, you can create informative boxplots to help visualize your data.