R for Data Science Cookbook

More Information
Learn
  • Get to know the functional characteristics of R language
  • Extract, transform, and load data from heterogeneous sources
  • Understand how easily R can confront probability and statistics problems
  • Get simple R instructions to quickly organize and manipulate large datasets
  • Create professional data visualizations and interactive reports
  • Predict user purchase behavior by adopting a classification approach
  • Implement data mining techniques to discover items that are frequently purchased together
  • Group similar text documents by using various clustering methods
About

This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently.

The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation is provided, illustrating how to use the “dplyr” and “data.table” packages to efficiently process larger data structures. We also focus on “ggplot2” and show you how to create advanced figures for data exploration.

In addition, you will learn how to build an interactive report using the “ggvis” package. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction.

By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing data analysis.

Features
  • Gain insight into how data scientists collect, process, analyze, and visualize data using some of the most popular R packages
  • Understand how to apply useful data analysis techniques in R for real-world applications
  • An easy-to-follow guide to make the life of data scientist easier with the problems faced while performing data analysis
Page Count 452
Course Length 13 hours 33 minutes
ISBN 9781784390815
Date Of Publication 28 Jul 2016

Authors

Yu-Wei, Chiu (David Chiu)

Yu-Wei, Chiu (David Chiu) is the founder of LargitData Company. He has previously worked for Trend Micro as a software engineer, with the responsibility of building up big data platforms for business intelligence and customer relationship management systems. In addition to being a startup entrepreneur and data scientist, he specializes in using Spark and Hadoop to process big data and apply data mining techniques to data analysis. Yu-Wei is also a professional lecturer, and has delivered talks on Python, R, Hadoop, and tech talks at a variety of conferences.

In 2013, Yu-Wei reviewed Bioinformatics with R Cookbook, a book compiled for Packt Publishing.