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Hands-On Exploratory Data Analysis with Python

You're reading from   Hands-On Exploratory Data Analysis with Python Perform EDA techniques to understand, summarize, and investigate your data

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789537253
Length 352 pages
Edition 1st Edition
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Authors (2):
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Suresh Kumar Mukhiya Suresh Kumar Mukhiya
Author Profile Icon Suresh Kumar Mukhiya
Suresh Kumar Mukhiya
Usman Ahmed Usman Ahmed
Author Profile Icon Usman Ahmed
Usman Ahmed
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Table of Contents (17) Chapters Close

Preface 1. Section 1: The Fundamentals of EDA
2. Exploratory Data Analysis Fundamentals FREE CHAPTER 3. Visual Aids for EDA 4. EDA with Personal Email 5. Data Transformation 6. Section 2: Descriptive Statistics
7. Descriptive Statistics 8. Grouping Datasets 9. Correlation 10. Time Series Analysis 11. Section 3: Model Development and Evaluation
12. Hypothesis Testing and Regression 13. Model Development and Evaluation 14. EDA on Wine Quality Data Analysis 15. Other Books You May Enjoy Appendix

Understanding unsupervised learning

Unsupervised machine learning deals with unlabeled data. This type of learning can discover all kinds of unknown patterns in the data and can facilitate useful categorization. Consider a scenario where patients use an online web application to learn about a disease, learn about their symptoms, and manage their illness. Such web applications that provide psychoeducation about certain diseases are referred to as Internet-Delivered Treatments (IDT). Imagine several thousand patients accessing the website at different timestamps of the day, learning about their illness, and all their activities are being logged into our database. When we analyze these log files and plot them using a scatter plot, we find a large group of patients who are accessing the website in the afternoon and a large chunk accessing the website in the evening. Some other patients...

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