Add aov = revenue ÷ orders (average order value) to monthly and draw it per month as a seaborn barplot, titled Average order value.
import pandas as pd
monthly = pd.DataFrame({
"month": ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"],
"revenue": [420, 380, 510, 560, 600, 580, 640, 700, 660, 820, 950, 1100],
"orders": [210, 190, 240, 260, 275, 270, 290, 310, 300, 360, 410, 470],
"ad_spend": [60, 55, 70, 75, 80, 78, 85, 90, 88, 110, 130, 150],
"returns": [12, 10, 15, 14, 18, 16, 17, 20, 19, 25, 30, 34],
})
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.