# Box Plot in Python using Matplotlib A box plot is a graphical representation of data that uses the median and quartiles of the data to represent the whole. It is a way of summarizing a set of data by creating a five-number summary of the data set. The five-number summary includes the median and quartiles (Q1, Q2, and Q3). The box in the box plot is used to represent the interquartile range (IQR) of the distribution. Box plots are often used in statistical analysis and data visualization to compare distributions of data and to detect outliers. Matplotlib is a popular Python library used for data visualization and plotting. Matplotlib provides a box plot function, which can be used to create box plots from numerical data. This tutorial provides a step-by-step guide for creating box plots using Matplotlib. In this tutorial, we will learn how to use the box plot function in Matplotlib to create box plots of the distribution of a given data set. We will also learn how to customize the box plot in Python using Matplotlib.

Algorithm: 1. Import the necessary libraries: ```Python import matplotlib.pyplot as plt import numpy as np ``` 2. Generate random data: ```Python data = np.random.normal(4, 2, 1000) ``` 3. Create a box plot of the data: ```Python plt.boxplot(data, showmeans=True, meanline=True, showfliers=True) ``` 4. Show the box plot: ```Python plt.show() ```