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

Examining, Cleaning, and Filtering

This chapter will introduce you to techniques to identify and clean missing and erroneous data formats. Concepts such as data manipulation, wrangling, and reshaping will be covered in this chapter. We will also learn how to select and filter data along with handling time series and textual data. These methods will be demonstrated using R packages such as dplyr, tidyr, stringr, forcats, lubridate, hms, and blob.

In this chapter, we will be covering the following topics:

  • Reshaping and tidying up missing and erroneous data
  • Manipulating and mutating data
  • Selecting and filtering data
  • Cleaning and manipulating time series data
  • Handling complex textual data