During data analysis, it is often essential to cluster or group data together based on certain criteria. For example, an e-commerce store might want to group all the sales that were done during the Christmas period or the orders that were received on Black Friday. These grouping concepts occur in several parts of data analysis. In this chapter, we will cover the fundamentals of grouping techniques and how doing this can improve data analysis. We will discuss different groupby() mechanics that will accumulate our dataset into various classes that we can perform aggregation on. We will also figure out how to dissect this categorical data with visualization by utilizing pivot tables and cross-tabulations.
In this chapter, we will cover the following topics:
- Understanding groupby()
- Groupby mechanics
- Data aggregation
- Pivot tables and cross-tabulations
