Modern R Programming Cookbook

By : Jaynal Abedin

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.

Preface

What this book covers

What you need for this book

Free Chapter

Installing and Configuring R and its Libraries

Introduction

Installing and configuring base R in Windows

Installing and configuring base R in Linux

Installing and configuring RStudio IDE in Windows

Installing and configuring RStudio IDE in Linux

Installing and configuring R tools for Visual Studio in Windows

Installing R libraries from various sources

Installing a specific version of R library

Data Structures in R

Introduction

Creating a vector and accessing its properties

Creating a matrix and accessing its properties

Creating a data frame and accessing its properties

Creating an array and accessing its properties

Creating a list from a combination of vector, matrix, and data frame

Converting a matrix to a data frame and a data frame to a matrix

Writing Customized Functions

Introduction

Writing your first function in R

Writing functions with multiple arguments and use of default values

Handling data types in input arguments

Producing different output types and return values

Making a recursive call to a function

Handling exceptions and error messages

Conditional and Iterative Operations

Introduction

The use of the if conditional statement

The use of the if…else conditional operator

The use of the ifelse vectorised conditional operator

Writing a function using the switch operator

Comparing the performance of switch and series of the if…else statements

Using for loop for iterations

Vectorised operation versus for loop

R Objects and Classes

Introduction

Defining a new S3 class

Defining methods for the S3 class

Creating a generic function and defining a method for the S3 class

Defining a new S4 class

Defining methods for an S4 class

Creating a function to return an object of the S4 class

Querying, Filtering, and Summarizing

Introduction

Using the pipe operator for data processing

Efficient and fast summarization using the dplyr verbs

Using the customized function within the dplyr verbs

Using the select verb for data processing

Using the filter verb for data processing

Using the arrange verb for data processing

Using mutate for data processing

Using summarise to summarize dataset

R for Text Processing

Introduction

Extracting unstructured text data from a plain web page

Extracting text data from an HTML page

Extracting text data from an HTML page using the XML library

Extracting text data from PubMed

Importing unstructured text data from a plain text file

Importing plain text data from a PDF file

Pre-processing text data for topic modeling and sentiment analysis

Creating a word cloud to explore unstructured text data

Using regular expression in text processing

R and Databases

Introduction

Installing the PostgreSQL database server

Creating a new user in the PostgreSQL database server

Creating a table in a database in PostgreSQL

Creating a dataset in PostgreSQL from R

Interacting with the PostgreSQL database from R

Creating and interacting with the SQLite database from R

Parallel Processing in R

Introduction

Creating an XDF file from CSV input

Processing data as a chunk

Comparing computation time with data frame and XDF

Linear regression with larger data (rxFastLiner)

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Installing and configuring RStudio IDE in Linux

In this recipe, you will see how to install RStudio IDE in the Linux operating system. The RStudio IDE user interface will be the same as that in Windows, but the installation process is different. You will walk through the process with the appropriate screenshot.

Getting ready

To install RStudio IDE, the prior requirement is to install base R. Let's assume that base R is already installed on the computer. Now, visit the following web page and download the appropriate installer from the available list at https://www.rstudio.com/products/rstudio/ and store it in the home directory for convenience. Depending on the version of Linux, the executable file comes with the various formats. In this recipe, you will download the .deb file and store it in the home directory. Also, you can directly install it from the internet using the wget command with the appropriate link to the file such as https://download1.rstudio.org/rstudio-1.0.136-amd64.deb.

How to do it…

Once you have downloaded the appropriate executable file, you are ready to install it. Since, you have downloaded the .deb file, you will require gdebi-core to execute that file. Here are the steps to install gdebi-core and then install RStudio IDE:

To install gdebi-core, run the following command:

      sudo apt-get install gdebi-core

To download the RStudio IDE installer .deb file, run the following command:

      wget https://download1.rstudio.org/rstudio-1.0.136-amd64.deb

The preceding command would generate the following output:

To install the IDE, run the following command:

      sudo gdebi rstudio-1.0.136-amd64.deb

The preceding command will generate the following output:

In the preceding screenshot, the terminal is asking whether you want to install the software or not. Type y and hit the Enter button here. Once the installation process is completed, you will see the following screen in the Terminal:

During installation, make sure you are connected to the internet.

How it works...

First, the sudo apt-get install gdebi-core command helps you download and install the gdebi-core package into the Linux system. By using the wget command, you are actually downloading the necessary file to install RStudio from the RStudio website. After that when you enter the sudo gdebi rstudio-1.0.136-amd64.deb command, it installs the software for you, and after completing this step, you are ready to use it.

Modern R Programming Cookbook

By : Jaynal Abedin

Modern R Programming Cookbook

By: Jaynal Abedin

Overview of this book

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