Book Image

Hands-On Exploratory Data Analysis with R

By : Radhika Datar, Harish Garg
Book Image

Hands-On Exploratory Data Analysis with R

By: Radhika Datar, Harish Garg

Overview of this book

Hands-On Exploratory Data Analysis with R will help you build a strong foundation in data analysis and get well-versed with elementary ways to analyze data. You will learn how to understand your data and summarize its characteristics. You'll also study the structure of your data, and you'll explore 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 set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using 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, uncover hidden insights, and present your results in a business context.
Table of Contents (17 chapters)
Free Chapter
1
Section 1: Setting Up Data Analysis Environment
7
Section 2: Univariate, Time Series, and Multivariate Data
11
Section 3: Multifactor, Optimization, and Regression Data Problems
14
Section 4: Conclusions

Manipulating data

Before you can start exploring your data, you first need to import it into your data analysis environment. There are many types of data, ranging from plain data in comma-separated value files to binary data in databases. Different R packages are equipped to handle these different kinds of data expertly and to import them almost ready for use in our environment. Since we are using R and RStudio, we will describe some of the most powerful R packages to import data in the following sections:

  • readr: readr can be used to read flat, rectangular data into R. It works with both comma-separated and tab-separated values.
  • readxl: We can use the readxl package to read data from MS Excel files.
  • jsonlite: Web services have increasingly started to provide data in a JSON format. The jsonlite package is a good way to import this kind of data into R.
  • httr, rvest: httr, and rvest...