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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