Exploratory Data Analysis with R

Exploratory Data Analysis with R Front Cover
2015-06-23
125 pages

Book Description

This book covers some of the basics of visualizing data in R and summarizing high dimensional data with statistical multivariate techniques. There is less of an emphasis on formal statistical inference methods, as inference is typically not the focus of EDA. Rather, the goal is to show the data, summarize the evidence and identify interesting while eliminating ideas that likely won’t pan out.

Throughout the book, we will focus on the R statistical programming language. We will cover the various plotting systems in R and how to use them effectively. We will also discuss how to implement dimension reduction techniques like clustering and the singular value decomposition. All of these techniques will help you to visualize your data and to help you make key decisions in any .

Table of Contents

  • Getting Started with R
  • Managing Data Frames with the dplyr package
  • Exploratory Data Analysis Checklist
  • of Analytic
  • Exploratory Graphs
  • Plotting Systems
  • Graphics Devices
  • The Base Plotting System
  • Plotting and Color in R
  • Hierarchical Clustering
  • K-Means Clustering
  • Dimension Reduction
  • The ggplot2 Plotting System: Part 1
  • The ggplot2 Plotting System: Part 2
  • Data Analysis Case Study: Changes in Fine Particle Pollution in the U.S.

Book Details

  • Title: Exploratory Data Analysis with R
  • Author:
  • Length: 125 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2015-06-23
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