
The Data Analysis Workshop
Solve business problems with state-of-the-art data analysis models, developing expert data analysis skills along the way
Packt Publishing
Published on 29. July 2020
Book
Paperback/Softback
626 pages
978-1-80107-028-7 (ISBN)
Description
Learn how to analyze data using Python models with the help of real-world use cases and guidance from industry experts
Key Features
Get to grips with data analysis by studying use cases from different fields
Develop your critical thinking skills by following tried-and-true data analysis
Learn how to use conclusions from data analyses to make better business decisions
Book DescriptionBusinesses today operate online and generate data almost continuously. While not all data in its raw form may seem useful, if processed and analyzed correctly, it can provide you with valuable hidden insights. The Data Analysis Workshop will help you learn how to discover these hidden patterns in your data, to analyze them, and leverage the results to help transform your business.
The book begins by taking you through the use case of a bike rental shop. You'll be shown how to correlate data, plot histograms, and analyze temporal features. As you progress, you'll learn how to plot data for a hydraulic system using the Seaborn and Matplotlib libraries, and explore a variety of use cases that show you how to join and merge databases, prepare data for analysis, and handle imbalanced data.
By the end of the book, you'll have learned different data analysis techniques, including hypothesis testing, correlation, and null-value imputation, and will have become a confident data analyst.What you will learn
Get to grips with the fundamental concepts and conventions of data analysis
Understand how different algorithms help you to analyze the data effectively
Determine the variation between groups of data using hypothesis testing
Visualize your data correctly using appropriate plotting points
Use correlation techniques to uncover the relationship between variables
Find hidden patterns in data using advanced techniques and strategies
Who this book is forThe Data Analysis Workshop is for programmers who already know how to code in Python and want to use it to perform data analysis. If you are looking to gain practical experience in data science with Python, this book is for you.
Key Features
Get to grips with data analysis by studying use cases from different fields
Develop your critical thinking skills by following tried-and-true data analysis
Learn how to use conclusions from data analyses to make better business decisions
Book DescriptionBusinesses today operate online and generate data almost continuously. While not all data in its raw form may seem useful, if processed and analyzed correctly, it can provide you with valuable hidden insights. The Data Analysis Workshop will help you learn how to discover these hidden patterns in your data, to analyze them, and leverage the results to help transform your business.
The book begins by taking you through the use case of a bike rental shop. You'll be shown how to correlate data, plot histograms, and analyze temporal features. As you progress, you'll learn how to plot data for a hydraulic system using the Seaborn and Matplotlib libraries, and explore a variety of use cases that show you how to join and merge databases, prepare data for analysis, and handle imbalanced data.
By the end of the book, you'll have learned different data analysis techniques, including hypothesis testing, correlation, and null-value imputation, and will have become a confident data analyst.What you will learn
Get to grips with the fundamental concepts and conventions of data analysis
Understand how different algorithms help you to analyze the data effectively
Determine the variation between groups of data using hypothesis testing
Visualize your data correctly using appropriate plotting points
Use correlation techniques to uncover the relationship between variables
Find hidden patterns in data using advanced techniques and strategies
Who this book is forThe Data Analysis Workshop is for programmers who already know how to code in Python and want to use it to perform data analysis. If you are looking to gain practical experience in data science with Python, this book is for you.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 191 mm
ISBN-13
978-1-80107-028-7 (9781801070287)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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. 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. 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.
Content
Table of Contents
Bike Sharing Analysis
Absenteeism at Work
Analyzing Bank Marketing Campaign Data
Tackling Company Bankruptcy
Analyzing the Online Shopper's Purchasing Intention
Analysis of Credit Card Defaulters
Analyzing the Heart Disease Dataset
Analyzing Online Retail II Dataset
Analysis of the Energy Consumed by Appliances
Analyzing Air Quality
Bike Sharing Analysis
Absenteeism at Work
Analyzing Bank Marketing Campaign Data
Tackling Company Bankruptcy
Analyzing the Online Shopper's Purchasing Intention
Analysis of Credit Card Defaulters
Analyzing the Heart Disease Dataset
Analyzing Online Retail II Dataset
Analysis of the Energy Consumed by Appliances
Analyzing Air Quality