Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
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

Generating Summary Statistics

In the world of data analysis, working with tabular data is a common practice. When analyzing tabular data, we sometimes need to get some quick insights into the patterns and distribution of the data. These quick insights typically provide the foundation for additional exploration and analyses. We refer to these quick insights as summary statistics. Summary statistics are very useful in exploratory data analysis projects because they help us perform some quick inspection of the data we are analyzing.

In this chapter we’re going to cover some common summary statistics used on exploratory data analysis projects. We will cover the following topics in this chapter:

  • Analyzing the mean of a dataset
  • Checking the median of a dataset
  • Identifying the mode of a dataset
  • Checking the variance of a dataset
  • Identifying the standard deviation of a dataset
  • Generating the range of a dataset
  • Identifying the percentiles of a dataset...
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 £16.99/month. Cancel anytime