Case Study

Foodbasket Analytics

Analysing food affordability and cost-of-living pressure through basket-level pricing, category contribution, and dashboard-based insight generation.

Status In Progress
Role Data Analyst
Focus Food Affordability
Tools Python, Excel, Power BI / Streamlit

Project Summary

Foodbasket Analytics is a data analytics project focused on understanding how the cost of essential food items contributes to affordability pressure. Instead of only looking at individual food prices, the project analyses basket-level cost, category contribution, and patterns that can help explain where cost pressure comes from.

Problem Statement

Food prices are often discussed in broad terms, but people usually experience the impact through a full basket of essential items. This project aims to make that impact clearer by analysing how different food categories contribute to the total basket cost.

Why It Matters

A structured foodbasket analysis can support budgeting, affordability tracking, and better communication of cost-of-living pressure for students, households, and lower-income groups.

Planned Methodology

01

Collect or structure food price data for essential basket items.

02

Clean and prepare the dataset for analysis.

03

Create metrics such as total basket cost and category contribution.

04

Build visualisations and dashboard views to communicate findings.

05

Summarise insights, limitations, and practical recommendations.

Expected Outputs

  • Cleaned food price dataset
  • Exploratory data analysis
  • Basket-level affordability metrics
  • Dashboard or visual report
  • Final insight summary

Skills Demonstrated

  • Data cleaning and preparation
  • Exploratory analysis
  • KPI and metric design
  • Dashboard storytelling
  • Business value communication