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R Data Analysis Cookbook - Second Edition

You're reading from  R Data Analysis Cookbook - Second Edition

Product type Book
Published in Sep 2017
Publisher Packt
ISBN-13 9781787124479
Pages 560 pages
Edition 2nd Edition
Languages
Authors (3):
Kuntal Ganguly Kuntal Ganguly
Profile icon Kuntal Ganguly
Shanthi Viswanathan Shanthi Viswanathan
Profile icon Shanthi Viswanathan
Viswa Viswanathan Viswa Viswanathan
Profile icon Viswa Viswanathan
View More author details
Toc

Table of Contents (14) Chapters close

Preface 1. Acquire and Prepare the Ingredients - Your Data 2. What's in There - Exploratory Data Analysis 3. Where Does It Belong? Classification 4. Give Me a Number - Regression 5. Can you Simplify That? Data Reduction Techniques 6. Lessons from History - Time Series Analysis 7. How does it look? - Advanced data visualization 8. This may also interest you - Building Recommendations 9. It's All About Your Connections - Social Network Analysis 10. Put Your Best Foot Forward - Document and Present Your Analysis 11. Work Smarter, Not Harder - Efficient and Elegant R Code 12. Where in the World? Geospatial Analysis 13. Playing Nice - Connecting to Other Systems

Generating reports of your data analysis with R Markdown and knitr

R Markdown provides you with a simple syntax to define analysis reports. Based on such a report definition, knitr can generate reports in HTML, PDF, Microsoft Word format, and several presentation formats. R Markdown documents contain regular text, embedded R code chunks, and inline R code. knitr parses the markdown document and inserts the results of executing the R code at specified locations within regular text to produce a well-formatted report.

R Markdown extends the regular markdown format to enable us to embed R code.

We can create R Markdown documents either in RStudio or directly in R using the markdown package. In this recipe, we will describe the RStudio approach.

Getting ready

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