FreeCampus Python

Milestone Challenge: Explain a Change in Library Visits

Compare incomplete observations and communicate a finding without claiming causation.

↗ Open in Colab

• Goal: Compare incomplete observations and communicate a finding without claiming causation.
• Estimated time: 2–4 hours of active work.
• Before starting: Complete the milestone units and their unit challenges.
• Keep: Your source, observed outputs, checks, and a debugging note.

Open this lesson in Google Colab

This community challenge is ungraded. Use the checks to review your own work; there is no submission service or automatic grade. Completion is self-reported in this browser on this device.

1. Explain a change in library visits

Week 1 visits Monday to Friday are 10, 20, 15, 25, 30; week 2 values are 12, 18, missing, 30, 40. A new display opened in week 2. Preserve missingness, compare the four matched days, and also report incomplete raw weekly totals. Create a day-by-day plot and a report for a volunteer.

Predict an ordinary result before coding. Start with the smallest part you can run and inspect. Use Colab for notebooks and the local workspace introduced in the units for packaging or command-line tasks.

2. Set up the experiment

import pandas as pd

visits = pd.DataFrame({
    "day": ["Mon", "Tue", "Wed", "Thu", "Fri"],
    "week_1": [10, 20, 15, 25, 30],
    "week_2": [12, 18, None, 30, 40],
})
# Compare raw totals and matched days explicitly.

The starter is deliberately incomplete. Implement the contract; do not change the expected results to match an incorrect implementation.

3. Check the observable results

1. Week 1 has five observations totaling 100; week 2 has four observed values totaling 100.
2. Matched-day totals are 85 and 100: an increase of 15, approximately 17.65%.
3. Wednesday remains missing in the source and plot, not zero.
4. Report counts with totals and explain why raw totals are not a like-for-like comparison.

Record actual outputs beside predictions. Reduce a failure to a small example, change one cause at a time, and repeat the failed check after repairing it.

4. Change one condition

Recover Wednesday as 5 in one scenario and 35 in another. Recompute complete weekly comparisons. Explain how a conclusion based only on the original totals could mislead.

5. Review a hint after attempting the task

Hint: connect the relevant tools

Apply a matched-day mask before comparable aggregation. Keep recovered-value scenarios separate from observed data and annotate missingness.

6. Explain and self-review

Deliver the notebook, missingness audit, comparison table, plot, and a 150-word report. Mention weather, events, and recording differences as reasons the observation alone cannot establish the display caused the change.

Review path: compare your result with the contract

Check the ordinary result first, then the boundary cases and changed condition. Explain which rule justifies each result. An implementation that differs from the hint can still satisfy the contract; explain why yours does.

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7. Save your work and record completion

Save the notebook or project somewhere you control. Include one decision, one failed check, its repair, and a result you can reproduce. Record completion after reviewing the checks; you can undo it later.

Not yet recorded.

Return to the milestone overview.