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

Exporting and customizing reports

We will now focus on customizing the reports with export functionality in the required format. The best illustration of the export format can be considered using the PDF format. We will carry out the following steps to create the export in PDF format:

  1. Create a Markdown document with a default output format in PDF, as shown in the following screenshot:
  1. The Markdown is created with the required attributes of title, author, the output format, and the date format, as follows:
  1. We can implement the same functions that were used in the previous example, while creating the required HTML documents, that is, fetching the summary of data and plotting the attributes, which is considered as a scatter plot:
> summary(Autompg)
mpg cylinders displacement horsepower weight acceleration
Min. : 9.00 Min. :3.000 Min. : 68.0 150 : 22 Min. :1613 Min. :...