Project 30: Signups Data Pipeline

Data Engineer

Current Task

Objective

Capstone: generate data, aggregate it, sort it, and filter it — a complete, realistic mini data pipeline using nothing but NumPy.

Task: seed the generator with 0, simulate 30 days of signups (5-50/day), then print the total, the best day (1-indexed), the top 5 days sorted descending, and how many days beat the average.

index.py

import numpy as np

np.random.seed(0)
daily_signups = np.random.randint(5, 50, size=30)

total_signups = np.sum(daily_signups)
best_day = np.argmax(daily_signups) + 1
sorted_signups = np.sort(daily_signups)[::-1]
above_average = daily_signups[daily_signups > daily_signups.mean()]

print(total_signups)
print(best_day)
print(sorted_signups[:5])
print(len(above_average))

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

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