[Solved] You have a nested list representing monthly sales for 3 stores over 4 months:sales = [[100, 120, 130, 140], [90, 110, 115, 130], [80, 105, 125, 135]]How can you create a numpy array and find the... | NumPy

NumPy - Creating Arrays

You have a nested list representing monthly sales for 3 stores over 4 months:

sales = [[100, 120, 130, 140], [90, 110, 115, 130], [80, 105, 125, 135]]

How can you create a numpy array and find the average sales per month across all stores?

Aarr = np.array(sales); avg = arr.mean(axis=1)

Barr = np.array(sales); avg = arr.sum(axis=0)

Carr = np.array(sales); avg = arr.mean(axis=0)

Darr = np.array(sales); avg = arr.sum(axis=1)

Step-by-Step Solution

Solution:

Step 1: Convert list to numpy array
Use np.array(sales) to create a 2D array with shape (3,4).
Step 2: Calculate average per month
Use mean(axis=0) to average over stores (rows) for each month (columns).
Final Answer:
arr = np.array(sales); avg = arr.mean(axis=0) -> Option C
Quick Check:
axis=0 averages columns (months) [OK]

Quick Trick: Use mean(axis=0) to average columns in 2D array [OK]

Common Mistakes:

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