Book Image

R for Data Science

By : Dan Toomey
Book Image

R for Data Science

By: Dan Toomey

Overview of this book

Table of Contents (19 chapters)



  • How does using lowercase help in analyzing text?

  • Why are there so many sparse entries? Does this number make sense?

  • Determine how to order the instructors matrix.

When, how, and why?

  • How would you remove the Unicode sequences from the text?

  • In what list of terms would you be interested in finding associations?

  • How could you adjust the course credits to be inclusive of the ranges of credits?


  • Can you determine the benefit of using word stems in the analysis?

  • Can you figure out how to display the actual text words in the dendogram rather than their index point?

  • Is there a way to convert a non-heterogeneous XML dataset to a matrix?