India Export Trade Dataset (HS2 Level, 2010–2021)

This dataset contains annual export trade data for India from 2010 to 2021 at the HS2 (Harmonized System 2-digit) commodity classification level. It includes commodity codes, export values, and associated reporting year information. The dataset has undergone a structured exploratory data analysis workflow including duplicate removal, HS code normalization, numeric validation of export values, missing value handling, and anomaly detection for extreme trade spikes. Year fields were standardized for chronological consistency. The final dataset is exported in a clean, analytics-ready CSV format suitable for econometric modeling, time-series forecasting, and trade performance analysis.

Data Quality

The dataset is structured in a normalized tabular format with consistent column naming and validated data types. Duplicate commodity-year entries have been removed to preserve data integrity. Export values have undergone range validation to eliminate negative or unrealistic entries. HS2 commodity codes were standardized to maintain classification consistency. The dataset is optimized for panel-data modeling and economic analysis, ensuring reliability for statistical and forecasting applications.

Use Cases

This dataset can be used for export trend analysis, commodity-level performance benchmarking, and economic forecasting. Economists and analysts can evaluate year-over-year export growth across commodity sectors. Policymakers can analyze trade diversification and sector contribution to overall exports. Data scientists can build predictive models for trade forecasting and volatility analysis. The dataset also supports dashboard development and sectoral competitiveness research.

Limitations

The dataset is community-sourced and may not represent official government statistical releases. It reflects annual trade summaries and does not include monthly breakdowns unless specified. It does not contain detailed destination-country trade splits in the selected file. The dataset is intended for research and analytics purposes and should not replace official trade publications.

Methodology

The dataset was prepared using a structured validation and normalization workflow that included schema standardization, duplicate removal, numeric validation of export values, and categorical normalization of HS2 commodity codes. Statistical anomaly detection was applied to identify extreme trade fluctuations that may indicate data inconsistencies. Year fields were verified for chronological continuity. The final dataset was exported in UTF-8 encoded CSV format to ensure compatibility with econometric tools, machine learning libraries, and business intelligence platforms.