---
product_id: 8101104
title: "Learning R: A Step-by-Step Function Guide to Data Analysis"
price: "€ 28.33"
currency: EUR
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reviews_count: 8
url: https://www.desertcart.ie/products/8101104-learning-r-a-step-by-step-function-guide-to-data
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---

# 146 rank in Mathematical & Statistical Software 189 reviews with 4.5-star rating Step-by-step guide to mastering R functions Learning R: A Step-by-Step Function Guide to Data Analysis

**Price:** € 28.33
**Availability:** ✅ In Stock

## Summary

> 📈 Unlock your data potential with the R guide that’s more than just code!

## Quick Answers

- **What is this?** Learning R: A Step-by-Step Function Guide to Data Analysis
- **How much does it cost?** € 28.33 with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.ie](https://www.desertcart.ie/products/8101104-learning-r-a-step-by-step-function-guide-to-data)

## Best For

- Customers looking for quality international products

## Why This Product

- Free international shipping included
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## Key Features

- • **Unique Coverage:** Includes rarely covered topics like factors and dates to boost your data handling edge.
- • **Practical & Applied:** Focuses on real-world data analysis applications, not just theory or dry coding.
- • **Boost Your Data Career:** Join hundreds of professionals who trust this guide to level up their R skills.
- • **Master R with Confidence:** A clear, intermediate-level walkthrough that balances programming and data analysis skills.
- • **Authoritative Yet Approachable:** Written in a friendly, easygoing style packed with actionable tips.

## Overview

Learning R: A Step-by-Step Function Guide to Data Analysis by Richard Cotton is a highly rated intermediate-level book that expertly bridges programming and practical data analysis. With a focus on applied techniques and unique topics like factors and dates, it empowers professionals to write better R code and perform insightful data analysis. Trusted by nearly 200 reviewers and ranked in top data science categories, this guide is a must-have for aspiring data analysts ready to elevate their skills beyond the basics.

## Description

Learning R: A Step-by-Step Function Guide to Data Analysis [Cotton, Richard] on desertcart.com. *FREE* shipping on qualifying offers. Learning R: A Step-by-Step Function Guide to Data Analysis

Review: Great introduction to R - This book is tremendous. It takes the reader through R without getting bogged down in an explanation of statistics and data modeling. It even includes chapters at the end on writing your own packages.
Review: but then your creativity as a data analyst will be limited and probably you will end up writing poor code. Alternatively focusin - If you want to start learning R, there several things you may want to consider. There are two kind of skills you want to cultivate: programming skills and actual data analysis ones. In principle, you can learn techniques alone, but then your creativity as a data analyst will be limited and probably you will end up writing poor code. Alternatively focusing only on coding may make you a good programmer, but it will be hard to get started on putting your skill into practice. Any book should strike a tradeoff in where to stand between training you in these two topics. Cotton's book try its best in this and does a pretty good job. The first part of the book, covering the intricacies of the language is the one I found most useful. I has all sort of good advise and explanations on the data structures and functions you can use. It is appropriately applied - not just about computation and programming, but actually links how they are applied in the actual data analysis. In this sense, this was the most original and interesting part of the book. The second part of the book, covering data analysis techniques was more conventional but still good. As such, there are perhaps better books if you are interested on any of the two sides ("machine learning for hackers" is very good to learn how to apply the techniques and seeing them in action; "Introduction to statistical learning" is a bit more theoretical; Advanced R or The Art of R Computing are unbeatable about teaching the language, although a bit dray). The approach of Cotton is really instructive. He is friendly, he write well in a easygoing fashion and the book is full of useful tips that helped me to understand how the language merge with the technique. The book is not encyclopedic, it does not cover every single topic (there are better books for that, Matloff and Wickhams books are better). Instead, it does a really good job as a tutorial that walks you through many topics that are somehow not covered in many other books -the chapter that covers factors and dates is perhaps not something you will deal with everyday, but very useful if you have to. Overall, I think the book teaches you really well how to play with the R language. A very final remark. I've seen other comments that suggest this is an introductory book. The book hardly takes things from scratch. If you have never written a line of code, you are likely to find it, particularly the first part, pretty dry. It is more an intermediate text, otherwise you will find yourself wondering why you need to know all these pages about data structures if you just want to learn to load a csv file and run a regression.

## Features

- Used Book in Good Condition

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #816,859 in Books ( See Top 100 in Books ) #146 in Mathematical & Statistical Software #246 in Data Mining (Books) #361 in Data Processing |
| Customer Reviews | 4.5 out of 5 stars 189 Reviews |

## Images

![Learning R: A Step-by-Step Function Guide to Data Analysis - Image 1](https://m.media-amazon.com/images/I/91cadVk-fxL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Great introduction to R
*by K***R on December 24, 2016*

This book is tremendous. It takes the reader through R without getting bogged down in an explanation of statistics and data modeling. It even includes chapters at the end on writing your own packages.

### ⭐⭐⭐⭐ but then your creativity as a data analyst will be limited and probably you will end up writing poor code. Alternatively focusin
*by L***D on November 27, 2015*

If you want to start learning R, there several things you may want to consider. There are two kind of skills you want to cultivate: programming skills and actual data analysis ones. In principle, you can learn techniques alone, but then your creativity as a data analyst will be limited and probably you will end up writing poor code. Alternatively focusing only on coding may make you a good programmer, but it will be hard to get started on putting your skill into practice. Any book should strike a tradeoff in where to stand between training you in these two topics. Cotton's book try its best in this and does a pretty good job. The first part of the book, covering the intricacies of the language is the one I found most useful. I has all sort of good advise and explanations on the data structures and functions you can use. It is appropriately applied - not just about computation and programming, but actually links how they are applied in the actual data analysis. In this sense, this was the most original and interesting part of the book. The second part of the book, covering data analysis techniques was more conventional but still good. As such, there are perhaps better books if you are interested on any of the two sides ("machine learning for hackers" is very good to learn how to apply the techniques and seeing them in action; "Introduction to statistical learning" is a bit more theoretical; Advanced R or The Art of R Computing are unbeatable about teaching the language, although a bit dray). The approach of Cotton is really instructive. He is friendly, he write well in a easygoing fashion and the book is full of useful tips that helped me to understand how the language merge with the technique. The book is not encyclopedic, it does not cover every single topic (there are better books for that, Matloff and Wickhams books are better). Instead, it does a really good job as a tutorial that walks you through many topics that are somehow not covered in many other books -the chapter that covers factors and dates is perhaps not something you will deal with everyday, but very useful if you have to. Overall, I think the book teaches you really well how to play with the R language. A very final remark. I've seen other comments that suggest this is an introductory book. The book hardly takes things from scratch. If you have never written a line of code, you are likely to find it, particularly the first part, pretty dry. It is more an intermediate text, otherwise you will find yourself wondering why you need to know all these pages about data structures if you just want to learn to load a csv file and run a regression.

### ⭐⭐⭐⭐⭐ Well written and easy to follow
*by M***L on August 23, 2015*

Well written and easy to follow. I very much appreciated the questions at the end of each segment testing ones ability to practice the material. I would highly recommend this book

## Frequently Bought Together

- Learning R: A Step-by-Step Function Guide to Data Analysis
- Hands-On Programming with R: Write Your Own Functions and Simulations
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

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*Last updated: 2026-03-13*