Mastering Python for Data Science

Data cleansing

The data in its raw form generally requires some cleaning so that it can be analyzed or a dashboard can be created on it. There are many reasons that data might have issues. For example, the Point of Sale system at a retail shop might have malfunctioned and inputted some data with missing values. We'll be learning how to handle such data in the following section.

Checking the missing data

Generally, most data will have some missing values. There could be various reasons for this: the source system which collects the data might not have collected the values or the values may never have existed. Once you have the data loaded, it is essential to check the missing elements in the data. Depending on the requirements, the missing data needs ...