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R for Data Science Cookbook (n) Cover

R for Data Science Cookbook (n)

Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques

Publisher:Packt Publishing Limited
By: Yu-Wei, Chiu (David Chiu)  
Paid access
|Sep 2025
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Over 100 hands-on recipes to effectively solve real-world data problems using the most popular R packages and techniques

Key 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

Book Description

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.

What you will 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

Who this book is for

This book is for those who are already familiar with the basic operation of R, but want to learn how to efficiently and effectively analyze real-world data problems using practical R packages.

Table of Contents

  1. Functions in R
  2. Data Extracting, Transforming and Loading
  3. Data Preprocess and Preparation
  4. Data Manipulation
  5. Visualizing Data with ggplot2
  6. Making Interactive Reports
  7. Simulation from Probability Distribution
  8. Statistical Inference in R
  9. Rule and Pattern Mining with R
  10. Time Series Mining with R
  11. Supervised Machine Learning
  12. Unsupervised Machine Learning
PDF ISBN: 978-1-78439-204-8
Publisher: Packt Publishing Limited
Copyright owner: © 2016 Packt Publishing Limited
Publication date: 2025
Language: English
Pages: 452
Related subjects:
Computer sciences,
Databases and data mining

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