Transforming data to fit analytic needs

In the previous section, you learned how to extract data and import it into R from various sources. Now you can transform it to create subsets of the data. This is useful to provide other team members with a portion of the data they can use in their work without requiring the complete dataset. In this section, you will learn the following four key activities associated with transformation:

  • Filtering data rows
  • Selecting data columns
  • Adding a calculated column from existing data
  • Aggregating data into groups

You will learn how to use functions from the dplyr package to perform data manipulation. If you are familiar with SQL, then dplyr is similar in how it filters, selects, sorts, and groups data. If you are not ...

Get Introduction to R for Business Intelligence now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.