Python Machine Learning By Example - Second Edition

Getting started with two types of data – numerical and categorical

At first glance, the features in the preceding dataset are categorical, for example, male or female, one of four age groups, one of the predefined site categories, and whether or not the user is interested in sports. Such data is different from the numerical feature data we have worked with till now.

Categorical (also called qualitative) features represent characteristics, distinct groups, and a countable number of options. Categorical features may or may not have logical order. For example, household income from low, median, to high is an ordinal feature, while the category of an ad is not ordinal. Numerical (also called quantitative) features, on the other hand, have mathematical ...