
The Data Analysis Workshop
Description
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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
Other editions
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Persons
Robert Thas John is a data engineer with a career that spans two decades. He manages a team of data engineers, analysts, and machine learning engineers - roles that he has held in the past. He leads a number of efforts aimed at increasing the adoption of machine learning on embedded devices through various programs from Google Developers and ARM Ltd, which licenses the chips found in Arduinos and other microcontrollers.
He started his career as a software engineer with work that has spanned various industries. His first experience with embedded systems was in programming payment terminals. Contacted by Royluis on 30th Jan20
Content
Bike Sharing Analysis
Absenteeism at Work
Analyzing Bank Marketing Campaign Data
Tackling Company Bankruptcy
Analyzing the Online Shopper
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
System requirements
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