Couple.uk.csv -

: Work categories (e.g., full-time, retired). Income : Individual or combined gross earnings. Education : Qualification levels of each partner.

: Use a scatter plot to compare the earnings of Partner A vs. Partner B to identify trends in "breadwinning" roles.

: Survey data often has "Refused" or "Don't Know" entries. Decide whether to drop these or impute them based on the median. Couple.uk.csv

: How long the couple has been together. 2. Data Cleaning Steps

: Ages of both partners (often labeled as age_p1 , age_p2 ). : Work categories (e

: The file contains survey data—often derived from sources like the UK Household Longitudinal Study—capturing details about cohabiting or married couples. Key Variables :

To put together a guide for the file, you should focus on its role in analyzing demographic and relationship dynamics in the UK. This file is typically used in data science and sociology projects to explore factors like age gaps, income differences, and household structures. 1. Dataset Overview : Use a scatter plot to compare the earnings of Partner A vs

: Ensure categorical data like employment status is consistently labeled (e.g., "Full-time" vs "FT").