ChallengeConstructionPYTHON+20 XP

Data Science case 16: K-nearest neighbours for Construction

Scenario

You are a data professional. A road building company has an issue: staff want to label a new site_jobs record by its closest neighbours. As a Data Scientist, you are tasked to solve it.

Question

Use KNN to predict a label.

Your task

Read the problem
Write your solution in the editor
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Deliverable: KNN prediction
On success it is published as its own portfolio project

K-nearest neighboursData ScienceProblem solving

Read the simple theory: Root-cause analysis

Data Science · Problem Solving & Regression — question 16 of 30

Finish all 30 to earn a certificate

1. Choose your dataset

Pick an industry and a size. Your code and results change to match.

IndustrySize

📓 DataPro notebookcase-data-science-16.ipynbFileEditViewRunKernel: Python 3

[md]

Data Science case 16: K-nearest neighbours for Construction

Use KNN to predict a label.

In [1]:

Your code cell is below. Press Check my answer to run the cell — the result appears as Out [1].

python editorsite_jobs

Snippets

💡 Explain my whole code, line by line (hover any word in the editor for a tip)

🌈 In short — no coding words

📂 Opens the "site_jobs" table→✅ Shows you the answer

Altogether: this script runs top to bottom, one line at a time, building up the answer step by step.

Start typing to see suggestions. Press Enter to use one. Red marks show the line to fix. Drag a bottom corner horizontally and vertically to resize.

Type your code here ↓Tap or click inside the box to start

✍️ Tap here to type

Dataset & schema

site_jobs

IndustryDataset size

The tiny starter data. Bigger data scrolls.

Fields

job_id	site	workers
J1	Bridge	10
J2	School	6
J3	Bridge	14
J4	Road	8

Construction data only.

attempts: 0

▶ Output terminal

$ Press “Check my answer” — results appear here.

Your next steps

Each item turns green when your answer includes it.

1 left