We identify relevant features that can help improve our model's performance. We create new features, such as the average sales per customer and the sales growth rate.
import matplotlib.pyplot as plt
Next, we use Jupyter Notebook to explore and visualize our data. We create a histogram to understand the distribution of sales values. building data science solutions with anaconda pdf