Hands-On Exploratory Data Analysis with R
Packt Publishing Limited (Verlag)
978-1-78980-437-9 (ISBN)
Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills
Key Features
Speed up your data analysis projects using powerful R packages and techniques
Create multiple hands-on data analysis projects using real-world data
Discover and practice graphical exploratory analysis techniques across domains
Book DescriptionHands-On Exploratory Data Analysis with R will help you build not just a foundation but also expertise in the elementary ways to analyze data. You will learn how to understand your data and summarize its main characteristics. You'll also uncover the structure of your data, and you'll learn graphical and numerical techniques using the R language.
This book covers the entire exploratory data analysis (EDA) process—data collection, generating statistics, distribution, and invalidating the hypothesis. As you progress through the book, you will learn how to set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using tools such as DOE Scatter Plot and SML2010 for multifactor, optimization, and regression data problems.
By the end of this book, you will be able to successfully carry out a preliminary investigation on any dataset, identify hidden insights, and present your results in a business context.
What you will learn
Learn powerful R techniques to speed up your data analysis projects
Import, clean, and explore data using powerful R packages
Practice graphical exploratory analysis techniques
Create informative data analysis reports using ggplot2
Identify and clean missing and erroneous data
Explore data analysis techniques to analyze multi-factor datasets
Who this book is forHands-On Exploratory Data Analysis with R is for data enthusiasts who want to build a strong foundation for data analysis. If you are a data analyst, data engineer, software engineer, or product manager, this book will sharpen your skills in the complete workflow of exploratory data analysis.
Radhika Datar has more than 5 years' experience in software development and content writing. She is well versed in frameworks such as Python, PHP, and Java, and regularly provides training on them. She has been working with Educba and Eduonix as a training consultant since June 2016, while also working as a freelance academic writer in data science and data analytics. She obtained her master's degree from the Symbiosis Institute of Computer Studies and Research and her bachelor's degree from K. J. Somaiya College of Science and Commerce. Harish Garg is a Principal Software Developer, author, and co-founder of a software development and training company, Bignumworks. Harish has more than 19 years of experience in a wide variety of technologies, including blockchain, data science and enterprise software. During this time, he has worked for companies such as McAfee, Intel, etc.
Table of Contents
Setting Up Our Data Analysis Environment
Importing Diverse Datasets
Examining, Cleaning, and Filtering
Visualizing Data Graphically with ggplot2
Creating Aesthetically Pleasing Reports with knitr and R Markdown
Univariate and Control Datasets
Time Series Datasets
Multivariate Datasets
Multi-Factor Datasets
Handling Optimization and Regression Data Problems
Next Steps
| Erscheinungsdatum | 05.06.2019 |
|---|---|
| Verlagsort | Birmingham |
| Sprache | englisch |
| Maße | 75 x 93 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Software Entwicklung ► User Interfaces (HCI) | |
| ISBN-10 | 1-78980-437-X / 178980437X |
| ISBN-13 | 978-1-78980-437-9 / 9781789804379 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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