This project delves into the real-world impact of food price inflation across India by comparing market data of essential food items from June 2024 and June 2025. It aims to quantify the cost variations for basic food necessities across different states, highlighting the ground reality of rising or falling prices and their implications for Indian households.
📦 Products Analyzed: 9 essential food items: Tomato, Onion, Potato, Rice, Wheat, Mustard Oil, Sugar, Garlic, and Tur Dal.
🗺️ States Covered: Madhya Pradesh, Uttar Pradesh, Punjab, West Bengal.
🗓️ Timeline: Data collected spans from 15th May to 20th June for both 2024 and 2025.
📂 Format:
Long-format CSV, including columns such as Product Name, Price, State, and Year.
Data was meticulously collected through manual web scraping techniques from the following public sources to ensure realism and regional accuracy:
- Agmarknet
- CommodityOnline
- Napanta
- ChiniMandi
- Kisan Deals
Initial data cleaning and structuring were performed to ensure data quality, consistency, and readiness for analysis. This process involved [mention specific cleaning steps if you can, e.g., "handling missing values," "standardizing product names," "converting currency formats"].
This study offers a granular look at how everyday food prices affect Indian households by analyzing regional inflation and price variability. The insights derived from this project can support:
- Policymaking: Informing government initiatives related to food security and economic stability.
- Journalism: Providing data-driven insights for reporting on economic trends.
- Research: Serving as a foundational dataset for further academic and socio-economic studies.
Demonstrated Skills:
- Data Collection & Web Scraping: Manual data acquisition from diverse online sources.
- Data Cleaning & Pre-processing: Ensuring data quality and consistency.
- Data Analysis (Planned): Utilizing [SQL, Python (Pandas), Excel] for comparative analysis and trend identification.
- Data Visualization (Planned): Creating insightful dashboards using [Tableau, Power BI] for clear communication of findings.
- Detailed visualizations of year-over-year price trends for each commodity and state.
- Comprehensive state-wise comparisons of inflation rates and price fluctuations.
- Interactive dashboards (👀) providing dynamic insights into regional food price dynamics.
- [Potentially: "Insights into the most affected states/commodities and potential contributing factors."]
"Data is dull until you season it with purpose."