Top Products by Revenue

After understanding overall revenue movement, the next step is to identify which products contribute the most to total sales. This analysis helps businesses focus on high-performing product lines.

Code:

# Group sales by product line and calculate total revenue

top_products = df.groupby('PRODUCTLINE')['SALES'].sum().reset_index().sort_values(by='SALES', ascending=False)

top_products

plt.figure(figsize=(5,3))

sns.barplot(

data=top_products,

x='PRODUCTLINE',

y='SALES'

)

plt.title("Top Product Lines by Revenue")

plt.xticks(rotation=45)

plt.ylabel("Total Sales")

plt.show()

Insights:
The bar chart compares total revenue across different product lines. Bar charts are used because they make comparison simple and clear. Product lines with taller bars generate higher revenue, helping identify which products drive business growth.