Hands-On Data Preprocessing in Python

Chapter 11: Data Cleaning Level III – Missing Values, Outliers, and Errors

In level I, we cleaned up the table without paying attention to the data structure or the recorded values. In level II, our attention was to have a data structure that would support our analytic goal, but we still didn't pay much attention to the correctness or appropriateness of the recorded values. That is the objective of data cleaning level III. In data cleaning level III, we will focus on the recorded values and will take measures to make sure that three matters regarding the values recorded in the data are addressed. First, we will make sure missing values in the data have been detected, that we know why this has happened, and that appropriate measures have been ...