: Useful for showing the intersection of employment types between partners.
: Verify extreme income or age values to ensure they aren't data entry errors. 3. Suggested Analysis
: Ensure categorical data like employment status is consistently labeled (e.g., "Full-time" vs "FT"). Couple.uk.csv
: Effective for comparing household income levels across different UK regions if geographic data is included. 5. Common Tools
: Survey data often has "Refused" or "Don't Know" entries. Decide whether to drop these or impute them based on the median. : Useful for showing the intersection of employment
: How long the couple has been together. 2. Data Cleaning Steps
: Ages of both partners (often labeled as age_p1 , age_p2 ). Suggested Analysis : Ensure categorical data like employment
: Work categories (e.g., full-time, retired). Income : Individual or combined gross earnings. Education : Qualification levels of each partner.