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

Summary

In this chapter, we focused on the implementation of all the libraries of a univariate dataset, which holds a strong representation for time series creation. The best illustration considered in this chapter is the measurement of pollution with respect to parsimonious models with RH and AH. We have listed some of the various packages that are available for reading, in various kinds of attributes, within the dataset indicated in R. There are lots of different options, and even the options we have listed have a wide functionality that we are going to cover and use as we progress through the book.

In the next chapter, we will cover multivariate datasets. Multivariate datasets include a combination of fixed and continuous variables that help us with further exploratory analysis.