Given a dataset sorted in ascending order, quartiles are the values that split the given dataset into quarters. Quartiles refer to the three data points that divide the given dataset into four equal parts, such that each split makes 25% of the dataset. In terms of percentiles, the 25th percentile is referred to as the first quartile (Q1), the 50th percentile is referred to as the second quartile (Q2), and the 75th percentile is referred to as the third quartile (Q3).

Based on the quartile, there is another measure called inter-quartile range that also measures the variability in the dataset. It is defined as follows:

IQR is not affected by the presence of outliers. Let's get the IQR for the price column from the same dataframe we have been using so far:

price = df.price.sort_values()
Q1 = np.percentile(price, 25)
Q2 = np.percentile(price, 50)
Q3 = np.percentile(price, 75)

IQR = Q3 - Q1
IQR

The output of the preceding snippet is as follows:

8718.5

Next, let's visualize the quartiles using the box plot.