Great work! You now know how to calculate the quartiles of any dataset by hand and with NumPy.
Quartiles are some of the most commonly used descriptive statistics. For example, You might see schools or universities think about quartiles when considering which students to accept. Businesses might compare their revenue to other companies by looking at quartiles.
In fact quartiles are so commonly used that the three quartiles, along with the minimum and the maximum values of a dataset, are called the five-number summary of the dataset. These five numbers help you quickly get a sense of the range, centrality, and spread of the dataset.
We’ve plotted the first, second, and third quartiles on the histogram for our music dataset. Are they where you expected to see them?