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Project 21: Play Count Simulator

Data Engineer

Builds on these lessons

Current Task

Objective

NumPy generates the numeric data that libraries like Seaborn visualize — np.random.normal() samples from a normal (bell curve) distribution around a mean.

Task: seed the generator with 3, then generate 5 play counts from a normal distribution (mean 500, std 100), rounded to whole numbers.

index.py
import numpy as np np.random.seed(3) play_counts = np.random.normal(loc=500, scale=100, size=5) print(play_counts.round(0))

* Hint: Correct characters turn green, incorrect ones turn red.

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