O'Reilly logo

R Data Analysis Cookbook - Second Edition by Kuntal Ganguly

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Handling missing data

In most real-world problems, data is likely to be incomplete because of incorrect data entry, faulty equipment, or improperly coded data. In R, missing values are represented by the symbol NA (not available) and are considered to be the first obstacle in predictive modeling. So, it's always a good idea to check for missing data in a dataset before proceeding for further predictive analysis. This recipe shows you how to handle missing data.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required