Python practice: Array Filtering & Conditional Logic (np.where & np.select)

Given orders = np.array([45, 120, 85, 230, 15, 310]), filter orders >= 100 with orders[orders >= 100] and print high_vol:

Given scores = np.array([85, 92, 78, 65, 95]), count how many are >= 80 using np.sum(scores >= 80) and print the count:

Given balances = np.array([1500, -200, 3400, -50]), use np.where(balances >= 0, "Solvent", "Overdrawn") to classify accounts. Print status:

Given balances = np.array([1500, -200, 3400, -50]), cap negative balances at 0 using np.where(balances < 0, 0, balances). Print capped:

Given sales = np.array([45000, 120000, 85000, 250000]), assign tiers with np.select([sales >= 200000, sales >= 100000, sales >= 50000], ["Platinum", "Gold", "Silver"], default="Bronze"). Print tiers:

Given units = np.array([12, 25, 8, 30]) and prices = np.array([150, 220, 350, 180]), find units where (units >= 20) & (prices >= 200) and print matching units:

Given margins = np.array([0.15, 0.28, 0.32, 0.12]), tag as "High" if margins >= 0.25, else "Standard". Print tags:

Given scores = np.array([45, 75, 90]), categorize with np.select([scores >= 80, scores >= 60], ["Pass", "Retest"], default="Fail"). Print results: