Chapter 4 Transformations

In many situations you will need to transform and modify the raw values of your data.

Transformations are useful for many reasons, for example:

to change the scale of a variable from continuous to discrete
to linearize a variable that has a non-linear distribution
to make distributions more symmetric
to re-center the data (mean-center, or center by other reference value)
to stretch or compress the values (by standard deviation, by range, by eigenvalues)
to binarize or dummify a categorical variable

In this chapter, I will cover common transformations: