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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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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Toc

Table of Contents (14) Chapters Close

Questions


Factual

  • Use of hexbin to manipulate bivariate data has shown several tools. What bivariate data do you have that would benefit from an application using hexbin?

  • The ggplothas function has several other features that I did not explore in this chapter. Familiarize yourself with them.

When, how, and why?

  • The map functionality appears to be very robust. How might you change the map function calls used in the chapter to result in a clearer graphic presentation?

  • In the sugar/alcohol graphics, should we exclude the outlier values?

Challenges

  • Explore the use of the playwith tools to get a good idea about how the interaction works, especially the transfer of data between the external tool and R.

  • It was difficult to get any results from RgoogleMaps without running out of memory. I have to believe there is something worthwhile there to use.

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