Data Aggregation

In this lesson, an explanation is provided on data aggregation and its various techniques.

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The grouping and aggregating functions can sometimes seem similar, but they are actually consecutive steps in obtaining important insights about data. Data is first grouped using the groupby() clause explained in the previous lesson. Then, aggregating functions and techniques can be applied to fetch the required information from the data.


It is a process of applying operations on groups of data to extract useful insights. Let’s understand this with an example. Some random animals are defined with hypothetical legs, weight, height, and protein values. Our task is to compute the average amount of legs, weight, height, and protein a certain animal class can have.

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