Book Image

Modern R Programming Cookbook

By : Jaynal Abedin
Book Image

Modern R Programming Cookbook

By: Jaynal Abedin

Overview of this book

R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.
Table of Contents (10 chapters)

Importing plain text data from a PDF file

The source text data could come in a portable document format (.pdf). Scientific research papers usually comes in PDF format. If you want to perform text mining, then you need to import the text from the PDF file into the R environment before doing any processing. In this recipe, you will import text data from a PDF file.

Getting ready

To implement this recipe, you will need to install the pdftools library.

To install the required library, run the following code:


The source data for this recipe is given in the following three different PDF files containing three abstracts. The filenames are as follows:

  • abstract_1.pdf
  • abstract_2.pdf
  • abstract_3...