A box plot is a statistical data visualization technique for analyzing the distribution and patterns of numerical data points of a dataset. It represents quartile 1, quartile 3, median, maximum and minimum data points of a feature which helps to understand the distribution of the numerical values of a dataset. If you want to know how to visualize a box plot, this article is for you. In this article, I’ll walk you through how to visualize a box plot using the Python programming language.
Box Plot
The box portion of a box plot contains three lines:
- the first line in the top represents quartile 3 of the data points, which means that 75% of the data lies below this point;
- the second line in the middle represents the median value of the data points, which means that 50% of the data lies below this point;
- the third line in the box plot represents quartile 1 of the data points, which means that 25% of the data lies below this point;
- the two horizontal lines below and above the box are known as whisker lines, the above whisker represents maximum value, and the lower whisker represents minimum value.
I hope you now have understood what a box plot shows you about a numerical feature of a dataset. Now in the section below, I will take you through how to visualize a box plot using Python.
Box Plot using Python
I will start by importing the necessary Python libraries and a dataset that we can use to visualize box plots using Python:
import pandas as pd data = pd.read_csv("https://raw.githubusercontent.com/amankharwal/Website-data/master/Advertising.csv") print(data.head())
Unnamed: 0 TV Radio Newspaper Sales 0 1 230.1 37.8 69.2 22.1 1 2 44.5 39.3 45.1 10.4 2 3 17.2 45.9 69.3 9.3 3 4 151.5 41.3 58.5 18.5 4 5 180.8 10.8 58.4 12.9
Now below is how you can visualize a box plot using the Python programming language:
import plotly.express as px fig = px.box(data, y="TV") fig.show()

So this is how you can easily visualize box plots using Python.
Summary
A box plot represents quartile 1, quartile 3, median, maximum and minimum data points of a feature which helps to understand the distribution of the numerical features of a dataset. I hope you liked this article on visualizing a box plot using Python. Feel free to ask your valuable questions in the comments section below.