Add share = each row's revenue as a % of its region's total (use groupby(...).transform("sum")), then draw it with catplot (kind bar): x = product, y = share, one column per region.
import pandas as pd
sales = pd.DataFrame({
"region": ["North", "North", "North", "South", "South", "South", "East", "East", "East", "West", "West", "West"],
"product": ["Laptop", "Phone", "Tablet", "Laptop", "Phone", "Tablet", "Laptop", "Phone", "Tablet", "Laptop", "Phone", "Tablet"],
"units": [120, 300, 80, 150, 280, 60, 90, 220, 70, 160, 310, 95],
"revenue": [6000, 4500, 1600, 7500, 4200, 1200, 4500, 3300, 1400, 8000, 4650, 1900],
"rating": [4.2, 4.5, 3.9, 4.4, 4.1, 3.7, 4.0, 4.3, 3.8, 4.6, 4.4, 4.0],
})
import seaborn as sns
import matplotlib.pyplot as pltDraw the chart. It is checked on what it shows: the data, the title and axis labels, the legend and the category names. Size and fonts don't matter.
Each hint gives a little more help. Try on your own first.
Run your code to see the output here.