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

Plotting the distributions

Creating a matrix plot of the variables is also a good preliminary step to perform, since it will immediately let you see the shape and distributions of the variables, and well as point out any gaps in the data. After removing some of the columns from the dataframe that we know we are not going to use, we can see that out dataset is fairly clean, and that the variables line up pretty much as we expect. For example, Admit.Day.of.Week is fairly normally distributed, but we can see that there is a null in the number of people discharged at mid-week. Costs are skewed, with very high values (but with low occurrences) at the extremes:

df <- df[,-c(12,13,16,19,20,21)]
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