Knowledge graphs · recommendations
People you may know
🎓 School maths · Years 3–4Number — counting & comparing — Count shared items (mutual friends) and rank by how many.Maths by year →
The Case. How do apps suggest new friends? They look at the graph: your friends' friends who aren't your friends yet.
Your tools. Plain Python counts, for each stranger, how many of your friends they share.
Investigate. Press Run. People are ranked by how many mutual friends you have.
- More mutual friends → a stronger suggestion. That's the whole trick behind ‘People you may know’.
- Add more friendships and see who gets recommended.
your_code.py
Starting Python…
The Reveal
Starting Python… (first time only — a few seconds)
🗒️ Detective's notes
Bundles your findings, chart and code into one PDF you can keep, print or hand in.
🧩 How this code works
The tools it uses
- Matplotlib — your crayon box — it turns numbers into charts and pictures.
What this one does
- • It draws a bar chart — great for comparing amounts.
How to read it, top to bottom
- 1. Import — bring in the tools (listed above).
- 2. The data — the lists and numbers near the top. These are the bits you change.
- 3. The work — a little maths, or a loop that repeats a step.
- 4. Show it —
print(...)writes words;plt.show()draws the picture.
Use it for your own problems
- Change the numbers at the top and press Run — nothing breaks, so experiment!
- Ask your own version of the question — swap in your family, your scores, your week.
- The same tools work on any numbers — that's the superpower you're learning.
Need a hint?
A friend-of-a-friend who you don't already know is a good suggestion — especially if you share several friends.