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R for Data Science

You're reading from R for Data Science Learn and explore the fundamentals of data science with R

Product type Paperback

Published in Dec 2014

Last Updated in Feb 2025

Publisher

ISBN-13 9781784390860

Length 364 pages

Edition 1st Edition

Languages

R

Concepts

Data Science

Author (1):

Toomey

View More author details

Table of Contents (14) Chapters

Preface

1. Data Mining Patterns FREE CHAPTER

2. Data Mining Sequences

3. Text Mining

4. Data Analysis – Regression Analysis

5. Data Analysis – Correlation

6. Data Analysis – Clustering

7. Data Visualization – R Graphics

8. Data Visualization – Plotting

9. Data Visualization – 3D

10. Machine Learning in Action

11. Predicting Events with Machine Learning

12. Supervised and Unsupervised Learning

Index

Packages

In R, there are several packages available that provide plotting functionalities to the programmer. We will use the following packages in the examples:

car: With a name that is an acronym for Companion to Applied Regression, this package provides the regression tools
lattice: This package provides high-level data visualization
gclus: This package has functions to create scatter plots
MASS: This has support functions and datasets for Venables and Ripley's MASS
ggplot2: This contains the grammar of graphics

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Tech Concepts

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Authors (1)

Toomey

Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.

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