Visualizing distributions in your data
Exploring the distribution of your feature is very important to understand some key characteristics of it, such as its skewness, mean, median, and quantiles. You can easily visualize skewness by plotting a histogram. This type of chart groups your data into bins or buckets and performs counts on top of them. For example, Figure 5.7 shows a histogram for the age variable:
Figure 5.7 – Plotting distributions with a histogram
Looking at the histogram, you could conclude that most of the people are between 20 and 50 years old. You can also see a few people more than 60 years old. Another example of a histogram is shown in Figure 5.8, which plots the distribution of payments from a particular event that has different ticket prices. It aims to analyze how much money people are paying per ticket.
Figure 5.8 – Checking skewness with a histogram
