IntermediateFinancePYTHON+20 XP

Credit scoring: engineer a debt ratio feature

Scenario

You are a data scientist. Raw income and debt columns barely predict default. Credit risk analysts always reason in ratios, not absolutes.

Question

Make one useful clue called debt_to_income by dividing debt by income, while safely handling zero income.

Your task

Divide monthly_debt by monthly_income
Use a safe empty value when income is zero
Stop one unusually large value from overpowering the model

Feature engineeringPandasPython

Read the simple theory: Python

Intermediate · Data Filtering & Record Counting — question 1 of 30

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1. Choose your dataset

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

IndustrySize

📓 DataPro notebookds-fin-01.ipynbFileEditViewRunKernel: Python 3

[md]

Credit scoring: engineer a debt ratio feature

Make one useful clue called debt_to_income by dividing debt by income, while safely handling zero income.

In [1]:

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

python editorloan_applications

Snippets

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

🌈 In short — no coding words

📂 Opens the "loan_applications" 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

loan_applications

IndustryDataset size

The tiny starter data. Bigger data scrolls.

Fields

applicant_id	monthly_income	monthly_debt	defaulted
1	24000	6000	0
2	0	3200	1
3	18500	14800	1

attempts: 0

▶ Output terminal

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

Your next steps

Each item turns green when your answer includes it.

4 left

Creates the ratio
Guards divide-by-zero
Finds the 99th percentile
Caps the values