Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Exploratory Data Analysis with Python Cookbook

You're reading from   Exploratory Data Analysis with Python Cookbook Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data

Arrow left icon
Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781803231105
Length 382 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Ayodele Oluleye Ayodele Oluleye
Author Profile Icon Ayodele Oluleye
Ayodele Oluleye
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Chapter 1: Generating Summary Statistics 2. Chapter 2: Preparing Data for EDA FREE CHAPTER 3. Chapter 3: Visualizing Data in Python 4. Chapter 4: Performing Univariate Analysis in Python 5. Chapter 5: Performing Bivariate Analysis in Python 6. Chapter 6: Performing Multivariate Analysis in Python 7. Chapter 7: Analyzing Time Series Data in Python 8. Chapter 8: Analysing Text Data in Python 9. Chapter 9: Dealing with Outliers and Missing Values 10. Chapter 10: Performing Automated Exploratory Data Analysis in Python 11. Index 12. Other Books You May Enjoy

Performing univariate analysis using a boxplot

Just like the histogram, the boxplot (also known as the whisker plot) is a good candidate for visualizing a single continuous variable within our dataset. Boxplots give us a sense of the underlying distribution of our dataset through five key metrics. The metrics include the minimum, first quartile, median, third quartile, and maximum values.

Figure 4.3: Boxplot illustration

Figure 4.3: Boxplot illustration

In the preceding figure, we can see the following components of a boxplot:

  • The box: This represents the interquartile range (25th percentile/1st quartile to the 75th percentile/3rd quartile). The median is the line within the box and it is also referred to as the 50th percentile.
  • The whisker limits: The upper and lower whisker limits represent the range of values in our dataset which are not outliers. The position of the whiskers is calculated from the interquartile range (IQR), 1st quartile, and 3rd quartile. This is represented...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image