Data aggregation is a term known from relational databases. In a database query, we can group data by the value in a column or columns. We can then perform various operations on each of these groups. The pandas DataFrame has similar capabilities. We will generate data held in a Python dict and then use this data to create a pandas DataFrame. We will then practice the pandas aggregation features:
Food(also a string)
Price(a random float)
Number(a random integer between one and nine)
The use case is that we have the results for some sort of a consumer-purchase ...