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The Data Analysis Workshop

You're reading from   The Data Analysis Workshop Solve business problems with state-of-the-art data analysis models, developing expert data analysis skills along the way

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839211386
Length 626 pages
Edition 1st Edition
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Authors (3):
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Konstantin Palagachev Konstantin Palagachev
Author Profile Icon Konstantin Palagachev
Konstantin Palagachev
Konstantin Palagachev holds a Ph.D. in applied mathematics and optimization, with an interest in operations research and data analysis. He is recognized for his passion for delivering data-driven solutions and expertise in the area of urban mobility, autonomous driving, insurance, and finance. He is also a devoted coach and mentor, dedicated to sharing his knowledge and passion for data science.
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Gururajan Govindan Gururajan Govindan
Author Profile Icon Gururajan Govindan
Gururajan Govindan
LinkedIn
Gururajan Govindan is a data scientist, intrapreneur, and trainer with more than seven years of experience working across domains such as finance and insurance. He is also an author of The Data Analysis Workshop, a book focusing on data analytics. He is well known for his expertise in data-driven decision-making and machine learning with Python.
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Shubhangi Hora Shubhangi Hora
Author Profile Icon Shubhangi Hora
Shubhangi Hora
Shubhangi Hora is a data scientist, Python developer, and published writer. With a background in computer science and psychology, she is particularly passionate about healthcare-related AI, including mental health. Shubhangi is also a trained musician.
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Table of Contents (12) Chapters Close

Preface
1. Bike Sharing Analysis 2. Absenteeism at Work FREE CHAPTER 3. Analyzing Bank Marketing Campaign Data 4. Tackling Company Bankruptcy 5. Analyzing the Online Shopper's Purchasing Intention 6. Analysis of Credit Card Defaulters 7. Analyzing the Heart Disease Dataset 8. Analyzing Online Retail II Dataset 9. Analysis of the Energy Consumed by Appliances 10. Analyzing Air Quality Appendix

8. Analyzing Online Retail II Dataset

Overview

In this chapter, you will search for and deal with missing values, outliers, and anomalies within a given dataset. You will learn how to create new columns from existing columns, conduct exploratory data analysis, and design visualizations. You will also practice summarizing the insights provided by your data. This chapter aims to guide you through various data analysis techniques pertaining to a specific dataset—the Online Retail II dataset—and therefore, a specific domain.

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Authors (3)

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Profile icon Gururajan Govindan
Gururajan Govindan
LinkedIn icon Github icon
Gururajan Govindan is a data scientist, intrapreneur, and trainer with more than seven years of experience working across domains such as finance and insurance. He is also an author of The Data Analysis Workshop, a book focusing on data analytics. He is well known for his expertise in data-driven decision-making and machine learning with Python.
Read more
See other products by Gururajan Govindan
Profile icon Konstantin Palagachev
Konstantin Palagachev
Konstantin Palagachev holds a Ph.D. in applied mathematics and optimization, with an interest in operations research and data analysis. He is recognized for his passion for delivering data-driven solutions and expertise in the area of urban mobility, autonomous driving, insurance, and finance. He is also a devoted coach and mentor, dedicated to sharing his knowledge and passion for data science.
Read more
See other products by Konstantin Palagachev
Profile icon Shubhangi Hora
Shubhangi Hora
Shubhangi Hora is a data scientist, Python developer, and published writer. With a background in computer science and psychology, she is particularly passionate about healthcare-related AI, including mental health. Shubhangi is also a trained musician.
Read more
See other products by Shubhangi Hora
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