Data aggregation with pandas DataFrames

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:

  1. Seed the NumPy random generator to make sure that the generated data will not differ between repeated program runs. The data will have four columns:
    • Weather (a string)
    • 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 ...

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