HandsOn Exploratory Data Analysis with R,Used

HandsOn Exploratory Data Analysis with R,Used

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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 handson data analysis projects using realworld data Discover and practice graphical exploratory analysis techniques across domains Book DescriptionHandsOn 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) processdata 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 multifactor datasets Who this book is forHandsOn 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. 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 MultiFactor Datasets Handling Optimization and Regression Data Problems Next Steps

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We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.

Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.

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Warranty

We provide a 2-year limited warranty, from the date of purchase for all our products.

If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.

This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).

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