Skip to Content
Practical Predictive Analytics
book

Practical Predictive Analytics

by Ralph Winters
June 2017
Beginner to intermediate
576 pages
15h 22m
English
Packt Publishing
Content preview from Practical Predictive Analytics

Determining all of the subset groups

Since we have only looked at parts of the file (via head() or tail() functions), we do not know how many categories there are and how they differ in terms of health care coverage. So we will start off by looking at some of the groupings.

In previous chapters, we have used sql() and the aggregate() function to group data. For this example, we will use the dplyr package. One advange of the dplyr() package is that it can also be used with pipe syntax, which allows the result of one function to be passed to the next function without intermediate assignments:

library(dplyr) > > Attaching package: 'dplyr' > The following objects are masked from 'package:stats':> >     filter, lag > The following objects are masked ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Data Superstream: Analytics Engineering

Data Superstream: Analytics Engineering

Alistair Croll, Anna Filippova, Emilie Schario, Lewis Davies, Jacob Frackson, Benn Stancil, Nick Acosta, Elizabeth Caley
R: Predictive Analysis

R: Predictive Analysis

Tony Fischetti, Eric Mayor, Rui Miguel Forte
Python: Advanced Predictive Analytics

Python: Advanced Predictive Analytics

Ashish Kumar, Joseph Babcock

Publisher Resources

ISBN: 9781785886188Supplemental Content