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Hands-On Exploratory Data Analysis with R

You're reading from   Hands-On Exploratory Data Analysis with R Become an expert in exploratory data analysis using R packages

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789804379
Length 266 pages
Edition 1st Edition
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Authors (2):
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Radhika Datar Radhika Datar
Author Profile Icon Radhika Datar
Radhika Datar
Harish Garg Harish Garg
Author Profile Icon Harish Garg
Harish Garg
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Setting Up Data Analysis Environment
2. Setting Up Our Data Analysis Environment FREE CHAPTER 3. Importing Diverse Datasets 4. Examining, Cleaning, and Filtering 5. Visualizing Data Graphically with ggplot2 6. Creating Aesthetically Pleasing Reports with knitr and R Markdown 7. Section 2: Univariate, Time Series, and Multivariate Data
8. Univariate and Control Datasets 9. Time Series Datasets 10. Multivariate Datasets 11. Section 3: Multifactor, Optimization, and Regression Data Problems
12. Multi-Factor Datasets 13. Handling Optimization and Regression Data Problems 14. Section 4: Conclusions
15. Next Steps 16. Other Books You May Enjoy

Setting Up Our Data Analysis Environment

In this chapter, we will look at how Exploratory Data Analysis (EDA) benefits businesses and has a significant impact on almost all vertical markets.

EDA is nothing but a pattern of analyzing datasets to summarize their main features, mostly with visual methods. We will list the R packages and tools that are required to do EDA. We will also focus on the installation procedure and setting up the packages for the EDA environment from an R perspective.

The following topics will be covered in this chapter:

  • The benefits of EDA across vertical markets
  • The most popular R packages for EDA
  • Installing the required R packages and tools
You have been reading a chapter from
Hands-On Exploratory Data Analysis with R
Published in: May 2019
Publisher: Packt
ISBN-13: 9781789804379
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