India Monthly Onion Price Dataset (2016–2022)

This dataset contains structured monthly onion price records for India including date, market or region identifiers, and price values measured in standard units such as INR per kilogram or quintal. The dataset has been processed through a structured exploratory data analysis workflow including duplicate removal, date normalization, price range validation, and statistical anomaly detection. Outlier detection techniques were applied to identify unrealistic price spikes. Categorical attributes such as market name were standardized to ensure analytical consistency. The final dataset is exported in a clean CSV format optimized for econometric modeling, commodity forecasting, and inflation impact analysis.

Data Quality

The dataset is organized in a normalized tabular format with consistent column naming and validated numeric data types. Duplicate monthly entries have been removed to maintain time-series integrity. Onion price values have undergone statistical range validation to eliminate unrealistic entries. Date fields have been standardized to maintain chronological consistency. The dataset is analytics-ready and supports regression modeling, ARIMA forecasting, and agricultural price trend analysis.

Use Cases

This dataset can be used for onion price trend analysis, agricultural commodity forecasting, inflation impact modeling, and food economics research. Analysts can study seasonal price patterns and market volatility. Data scientists can build time-series forecasting models for commodity price prediction. Policymakers can evaluate price stability and supply chain shocks. The dataset also supports dashboard visualization for agricultural market monitoring and food inflation analytics.

Limitations

The dataset is community-sourced and may not reflect officially audited government price releases. It contains monthly aggregated data and does not include daily or intraday price fluctuations. Geographic granularity may be limited depending on the dataset structure. The dataset is intended for analytical and research purposes and should not replace official agricultural pricing publications.

Methodology

The dataset was prepared using a structured validation and normalization framework including schema standardization, duplicate removal, numeric range validation of onion prices, and categorical normalization of market identifiers. Statistical anomaly detection techniques were applied to identify extreme price spikes. Date fields were standardized to ensure chronological integrity across the multi-year time-series. The final dataset was exported in UTF-8 encoded CSV format to ensure compatibility with econometric tools, machine learning libraries, and business intelligence platforms.