📝 README Description

Consumer Price Index (CPI) Inflation Analysis is an Excel-based data analysis project that studies inflation trends across different sectors and consumption categories over multiple years. The project focuses on data cleaning, transformation, pivot analysis, and interactive dashboard creation to extract meaningful economic insights.

This project analyzes pre-COVID and post-COVID inflation patterns and compares price movements across categories such as food, housing, fuel, health, transport, and education.

📂 Dataset Overview

Time Period: 2013 onwards

Sector-wise data (Rural / Urban)

Category-wise CPI indices

COVID classification: Pre-COVID vs Post-COVID

🛠️ Tools & Skills Used

Microsoft Excel

Data Cleaning & Formatting

Pivot Tables & Pivot Charts

Unpivoting data (Power Query style logic)

Dashboard Design

Time-series analysis

Economic indicator analysis (CPI)

⚙️ Key Sheets Explained

Raw Data – Original CPI dataset

Cleaned_Data – Structured and formatted dataset for analysis

Pivot Table / Pivot 2 – Category-wise and year-wise aggregation

UNPIVOT_FINAL_Date – Normalized data for flexible analysis

Analysis – Insights and calculations

Dashboard – Interactive visual dashboard

CPI Basket – CPI category structure

📊 Key Analysis Performed

Year-wise CPI inflation trends

Category-wise inflation comparison (Food, Fuel, Housing, etc.)

Rural vs Urban inflation movement

Pre-COVID vs Post-COVID impact on CPI

Identification of high-inflation categories over time

💡 Key Learnings

Hands-on experience with real economic data

Advanced Excel data modeling

Dashboard storytelling with data

Understanding inflation behavior through CPI