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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

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781784390860
Length 364 pages
Edition 1st Edition
Languages
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Author (1):
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 Toomey Toomey
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Toomey
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Toc

Table of Contents (19) Chapters Close

R for Data Science
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Data Mining Patterns 2. Data Mining Sequences FREE CHAPTER 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

Questions


Factual

  • The barplot function has a number of optional parameters. It might be interesting to play with a dataset and the parameters.

  • When you are displaying a word cloud, the function might complain that some words might not fit. Determine whether there is a way that this can be overcome.

When, how, and why?

  • What is the best way to determine the number of bins to be used in the hexbin function?

  • It was very unclear when producing a stacked bar chart as to how to organize the data to arrive at the correct result. Select a dataset and produce a stacked chart that meets your needs.

Challenges

  • There are several packages to produce plots. How would you select one of the packages to use for your plotting needs?

  • If there was a package that extracted just the text from a web page, that would be of tremendous use for R programming. Investigate whether anyone has made such a package or at least taken the initial steps.

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