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  • Book Overview & Buying R for Data Science
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R for Data Science

R for Data Science

By : Toomey
3.4 (5)
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R for Data Science

R for Data Science

3.4 (5)
By: Toomey

Overview of this book

If you are a data analyst who has a firm grip on some advanced data analysis techniques and wants to learn how to leverage the features of R, this is the book for you. You should have some basic knowledge of the R language and should know about some data science topics.
Table of Contents (14 chapters)
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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.

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
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R for Data Science
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