Welcome to today's lesson! Our topic for the day is data aggregation, a crucial aspect of data analysis. Like summarizing a massive book into key points, data aggregation summarizes large amounts of data into important highlights.

By the end of today, you'll be equipped with several aggregation methods to summarize data streams in Python. Let's get started!

Let's say we have a list of numbers denoting the ages of a group of people:

Common questions we might ask: How many people are in the group? What's their total age? Who's the youngest and the oldest? Python's handy built-in functions len, sum, min, and max have our answers:

These functions provide essential aggregation operations and are widely used with data streams.

For deeper analysis, such as calculating the average age or range of ages, we resort to for and loops.