This chapter discusses how a developer might understand and approach the topic of data cleaning using several common statistical methods.
In this chapter, we've broken things into the following topics:
- Understanding basic data cleaning
- Using R to detect and diagnose common data issues, such as missing values, special values, outliers, inconsistencies, and localization
- Using R to address advanced statistical situations, such as transformation, deductive correction, and deterministic imputation