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RStudio for R Statistical Computing Cookbook

You're reading from RStudio for R Statistical Computing Cookbook Over 50 practical and useful recipes to help you perform data analysis with R by unleashing every native RStudio feature

Product type Paperback

Published in Apr 2016

Publisher

ISBN-13 9781784391034

Length 246 pages

Edition 1st Edition

Languages

R

Tools

RStudio

Concepts

Data Analysis

Author (1):

Andrea Cirillo

View More author details

Table of Contents (10) Chapters

Preface

1. Acquiring Data for Your Project

2. Preparing for Analysis – Data Cleansing and Manipulation FREE CHAPTER

3. Basic Visualization Techniques

4. Advanced and Interactive Visualization

5. Power Programming with R

6. Domain-specific Applications

7. Developing Static Reports

8. Dynamic Reporting and Web Application Development

Index

Introduction

This chapter introduces you to a few advanced programming techniques in R, leveraging some of the unique features of the RStudio IDE, such as the embedded Git pane (refer to the last recipe of this chapter, Using GitHub with RStudio, to know more).

The recipes accomplished in this chapter are usually encountered by R programmers when dealing with large datasets (refer to the Implementing parallel computation in R recipe) and optimization issues (refer to the recipes on the profvis and microbenchmarking packages).

The rest of the chapter is locked

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Authors (1)

Andrea Cirillo

Andrea Cirillo

Andrea Cirillo is currently working as an audit quantitative analyst at Intesa Sanpaolo Banking Group. He gained financial and external audit experience at Deloitte Touche Tohmatsu and internal audit experience at FNM, a listed Italian company. His main responsibilities involve the evaluation of credit risk management models and their enhancement, mainly within the field of the Basel III capital agreement. He is married to Francesca and is the father of Tommaso, Gianna, Zaccaria, and Filippo. Andrea has written and contributed to a few useful R packages such as updateR, ramazon, and paletteR, and regularly shares insightful advice and tutorials on R programming. His research and work mainly focus on the use of R in the fields of risk management and fraud detection, largely by modeling custom algorithms and developing interactive applications. Andrea has previously authored RStudio for R Statistical Computing Cookbook for Packt Publishing.

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