Your question is Handling 30% Missing Critical Data. Start with the requirements and the two tables on the right.
Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.
How would you handle a dataset where 30% of the entries are missing critical information at American Credit Acceptance?
For this exercise, evaluate completeness for each loan application source. Treat NULL or blank employment status, and NULL values in income, requested amount, or credit score as missing critical information.
source_name, total_entries, missing_entries, and missing_percentage.| Column | Type | Description |
|---|---|---|
| application_idPK | INT | Unique loan application identifier |
| source_id | INT | Identifier of the application submission source |
| annual_income | DECIMAL(12,2) | Applicant annual income |
| employment_status | VARCHAR(40) | Applicant employment status |
| requested_amount | DECIMAL(12,2) | Requested loan amount |
| credit_score | INT | Applicant credit score |
| Column | Type | Description |
|---|---|---|
| source_idPK | INT | Unique application source identifier |
| source_name | VARCHAR(60) | Name of the application submission source |