# Global Import-Export Top Product Routes (1995-2024)

Ranked exporter-importer routes for individual HS6 products, combining export performance with buyer demand, market share, competition, access, and route-risk indicators.

## What one row represents
one HS6 product and exporter-importer route

## Included measures and context
- Route ranking, trade values, and growth
- Buyer demand, supplier competition, and market share
- Tariff, volatility, and risk indicators

## Metric notes
- HS6 codes identify products at the six-digit Harmonized System level.
- CAGR is the compound annual growth rate across a multi-year period.
- HHI summarizes concentration; higher values indicate activity is concentrated among fewer participants.
- Year-over-year growth compares a value with the previous year; a negative percentage indicates a decline.
- Fields marked USD are monetary values denominated in US dollars.
- Values ending in pp are percentage-point changes.
- Values ending in pct are percentages.
- Country fields ending in ISO3 use three-letter ISO 3166-1 country codes.

## Fields
Column names are shown exactly as they appear in the Parquet file. The schema lists the same fields, and the sample file shows example values.

- `hs_code` — `string`
- `corridor_rank` — `uint16`
- `exporter_iso3` — `string`
- `importer_iso3` — `string`
- `latest_data_year` — `uint16`
- `lane_data_years` — `uint16`
- `exports_latest_observed_usd` — `float64`
- `exports_all_year_avg_usd` — `float64`
- `exports_avg_3y_usd` — `float64`
- `exports_avg_5y_usd` — `float64`
- `exports_avg_10y_usd` — `float64`
- `exports_cagr_3y_pct` — `float64`
- `exports_cagr_5y_pct` — `float64`
- `exports_cagr_10y_pct` — `float64`
- `exports_historical_peak_usd` — `float64`
- `buyer_imports_latest_observed_usd` — `float64`
- `historical_peak_year` — `uint16`
- `positive_growth_year_share_pct` — `float64`
- `trend_acceleration_pct` — `float64`
- `trend_label` — `string`
- `buyer_yoy_latest_pct` — `float64`
- `buyer_yoy_all_avg_pct` — `float64`
- `buyer_trend_consistency_pct` — `float64`
- `market_share_latest_pct` — `float64`
- `market_share_change_1y_pp` — `float64`
- `peer_best_share_pct` — `float64`
- `peer_top_exporter` — `string`
- `supplier_count_latest` — `uint16`
- `buyer_market_hhi` — `float64`
- `distance_km` — `float64`
- `has_reported_fta` — `uint8`
- `applied_tariff_pct` — `float64`
- `tariff_advantage_pp` — `float64`
- `volatility_cv` — `float64`
- `max_drawdown_pct` — `float64`
- `attention_level` — `string`
- `primary_risk_reason` — `string`
- `risk_driver_labels` — `List`
- `signal_flag` — `string`
- `confidence_label` — `string`
- `refreshed_at` — `timestamp[ms, tz=UTC]`

## Coverage and size
- Coverage: 1995-2024 annual observations where available
- Records: 477,118
- Parquet file size: 75 MB
- Release: 1.0.0
- SHA-256: `f84810211d27fc0234de8061697616b679747ee742cc63b9f1a461596b2ae88c`

## Files
- `data.parquet` — complete dataset
- `manifest.json` — dataset description, coverage, record count, and download details
- `schema.json` — field names, row definition, included measures, and metric notes
- `sample.json` — example records
- `README.md` — these notes

## Read the Parquet file with Python
```python
import pandas as pd

data = pd.read_parquet("data.parquet")
print(data.head())
```

Install `pandas` and `pyarrow` if they are not already available: `python -m pip install pandas pyarrow`.

## Sources and related files
- OECD BIMTS HS2017-6D
- Dataset page: https://www.yugalinks.com/datasets/import-export/import-export-top-product-routes-v1/
- Original dataset record: https://huggingface.co/datasets/yugalinks/import-export-top-product-routes-v1