exporter_iso3 stringclasses 257
values | exporter_iso3_dynamic stringclasses 266
values | exporter_name stringclasses 263
values | importer_iso3 stringclasses 257
values | importer_iso3_dynamic stringclasses 266
values | importer_name stringclasses 263
values | broad_sector stringclasses 4
values | industry_id uint16 1 170 | industry_descr stringclasses 170
values | year uint16 1.99k 2.02k | trade int64 0 4,675B | flag_mirror uint16 0 407 | flag_zero stringclasses 3
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
AFG | AFG | Afghanistan | ARE | ARE | United Arab Emirates | Agriculture | 1 | Wheat | 1,993 | 0 | 0 | u |
AFG | AFG | Afghanistan | ARE | ARE | United Arab Emirates | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AFG | AFG | Afghanistan | ARE | ARE | United Arab Emirates | Agriculture | 1 | Wheat | 2,007 | 0 | 0 | u |
AFG | AFG | Afghanistan | ARE | ARE | United Arab Emirates | Agriculture | 1 | Wheat | 2,008 | 0 | 0 | u |
AFG | AFG | Afghanistan | ARE | ARE | United Arab Emirates | Agriculture | 1 | Wheat | 2,009 | 0 | 0 | u |
AFG | AFG | Afghanistan | ARE | ARE | United Arab Emirates | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AFG | AFG | Afghanistan | ARE | ARE | United Arab Emirates | Agriculture | 1 | Wheat | 2,020 | 8,000 | 0 | p |
AFG | AFG | Afghanistan | BLR | BLR | Belarus | Agriculture | 1 | Wheat | 1,993 | 0 | 0 | u |
AFG | AFG | Afghanistan | BLR | BLR | Belarus | Agriculture | 1 | Wheat | 1,999 | 9,000 | 0 | p |
AFG | AFG | Afghanistan | BLR | BLR | Belarus | Agriculture | 1 | Wheat | 2,007 | 0 | 0 | u |
AFG | AFG | Afghanistan | BLR | BLR | Belarus | Agriculture | 1 | Wheat | 2,008 | 0 | 0 | u |
AFG | AFG | Afghanistan | BLR | BLR | Belarus | Agriculture | 1 | Wheat | 2,009 | 0 | 0 | u |
AFG | AFG | Afghanistan | BLR | BLR | Belarus | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AFG | AFG | Afghanistan | BLR | BLR | Belarus | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AFG | AFG | Afghanistan | MAR | MAR | Morocco | Agriculture | 1 | Wheat | 1,993 | 0 | 0 | u |
AFG | AFG | Afghanistan | MAR | MAR | Morocco | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AFG | AFG | Afghanistan | MAR | MAR | Morocco | Agriculture | 1 | Wheat | 2,007 | 0 | 0 | u |
AFG | AFG | Afghanistan | MAR | MAR | Morocco | Agriculture | 1 | Wheat | 2,008 | 41,373,000 | 0 | p |
AFG | AFG | Afghanistan | MAR | MAR | Morocco | Agriculture | 1 | Wheat | 2,009 | 18,438,000 | 0 | p |
AFG | AFG | Afghanistan | MAR | MAR | Morocco | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AFG | AFG | Afghanistan | MAR | MAR | Morocco | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AFG | AFG | Afghanistan | NGA | NGA | Nigeria | Agriculture | 1 | Wheat | 1,993 | 0 | 0 | u |
AFG | AFG | Afghanistan | NGA | NGA | Nigeria | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AFG | AFG | Afghanistan | NGA | NGA | Nigeria | Agriculture | 1 | Wheat | 2,007 | 3,306,000 | 0 | p |
AFG | AFG | Afghanistan | NGA | NGA | Nigeria | Agriculture | 1 | Wheat | 2,008 | 1,000 | 0 | p |
AFG | AFG | Afghanistan | NGA | NGA | Nigeria | Agriculture | 1 | Wheat | 2,009 | 0 | 0 | u |
AFG | AFG | Afghanistan | NGA | NGA | Nigeria | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AFG | AFG | Afghanistan | NGA | NGA | Nigeria | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AFG | AFG | Afghanistan | SVN | SVN | Slovenia | Agriculture | 1 | Wheat | 1,993 | 18,000 | 0 | p |
AFG | AFG | Afghanistan | SVN | SVN | Slovenia | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AFG | AFG | Afghanistan | SVN | SVN | Slovenia | Agriculture | 1 | Wheat | 2,007 | 0 | 0 | u |
AFG | AFG | Afghanistan | SVN | SVN | Slovenia | Agriculture | 1 | Wheat | 2,008 | 0 | 0 | u |
AFG | AFG | Afghanistan | SVN | SVN | Slovenia | Agriculture | 1 | Wheat | 2,009 | 0 | 0 | u |
AFG | AFG | Afghanistan | SVN | SVN | Slovenia | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AFG | AFG | Afghanistan | SVN | SVN | Slovenia | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AFG | AFG | Afghanistan | UZB | UZB | Uzbekistan | Agriculture | 1 | Wheat | 1,993 | 0 | 0 | u |
AFG | AFG | Afghanistan | UZB | UZB | Uzbekistan | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AFG | AFG | Afghanistan | UZB | UZB | Uzbekistan | Agriculture | 1 | Wheat | 2,007 | 0 | 0 | u |
AFG | AFG | Afghanistan | UZB | UZB | Uzbekistan | Agriculture | 1 | Wheat | 2,008 | 0 | 0 | u |
AFG | AFG | Afghanistan | UZB | UZB | Uzbekistan | Agriculture | 1 | Wheat | 2,009 | 0 | 0 | u |
AFG | AFG | Afghanistan | UZB | UZB | Uzbekistan | Agriculture | 1 | Wheat | 2,017 | 229,000 | 0 | p |
AFG | AFG | Afghanistan | UZB | UZB | Uzbekistan | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AGO | AGO | Angola | BGR | BGR | Bulgaria | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AGO | AGO | Angola | BGR | BGR | Bulgaria | Agriculture | 1 | Wheat | 2,010 | 0 | 0 | u |
AGO | AGO | Angola | BGR | BGR | Bulgaria | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AGO | AGO | Angola | BGR | BGR | Bulgaria | Agriculture | 1 | Wheat | 2,019 | 0 | 0 | u |
AGO | AGO | Angola | BGR | BGR | Bulgaria | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AGO | AGO | Angola | BGR | BGR | Bulgaria | Agriculture | 1 | Wheat | 2,022 | 1,000 | 0 | p |
AGO | AGO | Angola | BGR | BGR | Bulgaria | Agriculture | 1 | Wheat | 2,023 | 0 | 0 | r |
AGO | AGO | Angola | BRA | BRA | Brazil | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AGO | AGO | Angola | BRA | BRA | Brazil | Agriculture | 1 | Wheat | 2,010 | 2,298,000 | 0 | p |
AGO | AGO | Angola | BRA | BRA | Brazil | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AGO | AGO | Angola | BRA | BRA | Brazil | Agriculture | 1 | Wheat | 2,019 | 0 | 0 | u |
AGO | AGO | Angola | BRA | BRA | Brazil | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AGO | AGO | Angola | BRA | BRA | Brazil | Agriculture | 1 | Wheat | 2,022 | 0 | 0 | u |
AGO | AGO | Angola | BRA | BRA | Brazil | Agriculture | 1 | Wheat | 2,023 | 0 | 0 | u |
AGO | AGO | Angola | COD | COD | Congo, Democratic Republic of the | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AGO | AGO | Angola | COD | COD | Congo, Democratic Republic of the | Agriculture | 1 | Wheat | 2,010 | 0 | 0 | u |
AGO | AGO | Angola | COD | COD | Congo, Democratic Republic of the | Agriculture | 1 | Wheat | 2,017 | 1,000 | 0 | p |
AGO | AGO | Angola | COD | COD | Congo, Democratic Republic of the | Agriculture | 1 | Wheat | 2,019 | 0 | 0 | r |
AGO | AGO | Angola | COD | COD | Congo, Democratic Republic of the | Agriculture | 1 | Wheat | 2,020 | 180,000 | 1 | p |
AGO | AGO | Angola | COD | COD | Congo, Democratic Republic of the | Agriculture | 1 | Wheat | 2,022 | 1,000 | 1 | p |
AGO | AGO | Angola | COD | COD | Congo, Democratic Republic of the | Agriculture | 1 | Wheat | 2,023 | 0 | 0 | u |
AGO | AGO | Angola | GHA | GHA | Ghana | Agriculture | 1 | Wheat | 1,999 | 4,908,000 | 0 | p |
AGO | AGO | Angola | GHA | GHA | Ghana | Agriculture | 1 | Wheat | 2,010 | 0 | 0 | u |
AGO | AGO | Angola | GHA | GHA | Ghana | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AGO | AGO | Angola | GHA | GHA | Ghana | Agriculture | 1 | Wheat | 2,019 | 0 | 0 | u |
AGO | AGO | Angola | GHA | GHA | Ghana | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AGO | AGO | Angola | GHA | GHA | Ghana | Agriculture | 1 | Wheat | 2,022 | 0 | 0 | u |
AGO | AGO | Angola | GHA | GHA | Ghana | Agriculture | 1 | Wheat | 2,023 | 0 | 0 | u |
AGO | AGO | Angola | NAM | NAM | Namibia | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | r |
AGO | AGO | Angola | NAM | NAM | Namibia | Agriculture | 1 | Wheat | 2,010 | 0 | 0 | u |
AGO | AGO | Angola | NAM | NAM | Namibia | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AGO | AGO | Angola | NAM | NAM | Namibia | Agriculture | 1 | Wheat | 2,019 | 102,000 | 1 | p |
AGO | AGO | Angola | NAM | NAM | Namibia | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AGO | AGO | Angola | NAM | NAM | Namibia | Agriculture | 1 | Wheat | 2,022 | 0 | 0 | r |
AGO | AGO | Angola | NAM | NAM | Namibia | Agriculture | 1 | Wheat | 2,023 | 0 | 0 | u |
AGO | AGO | Angola | NLD | NLD | Netherlands | Agriculture | 1 | Wheat | 1,999 | 0 | 0 | u |
AGO | AGO | Angola | NLD | NLD | Netherlands | Agriculture | 1 | Wheat | 2,010 | 0 | 0 | u |
AGO | AGO | Angola | NLD | NLD | Netherlands | Agriculture | 1 | Wheat | 2,017 | 0 | 0 | u |
AGO | AGO | Angola | NLD | NLD | Netherlands | Agriculture | 1 | Wheat | 2,019 | 0 | 0 | u |
AGO | AGO | Angola | NLD | NLD | Netherlands | Agriculture | 1 | Wheat | 2,020 | 0 | 0 | u |
AGO | AGO | Angola | NLD | NLD | Netherlands | Agriculture | 1 | Wheat | 2,022 | 0 | 0 | r |
AGO | AGO | Angola | NLD | NLD | Netherlands | Agriculture | 1 | Wheat | 2,023 | 1,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 1,995 | 65,580,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 1,996 | 90,817,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 1,997 | 91,274,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 1,998 | 78,672,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 1,999 | 55,301,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,000 | 66,458,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,001 | 47,202,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,002 | 53,482,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,003 | 54,381,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,004 | 63,362,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,005 | 60,659,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,006 | 57,664,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,007 | 77,101,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,008 | 142,122,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,009 | 91,185,000 | 0 | p |
ALB | ALB | Albania | ALB | ALB | Albania | Agriculture | 1 | Wheat | 2,010 | 82,282,000 | 0 | p |
ITPD-E R2025 — compact parquet + lookup tables
A compact, analysis-ready copy of the USITC International Trade and Production Database for Estimation (ITPD-E), release 2025, plus lookup tables that link it to ISO / UN M49 country codes, World Bank income groups and the USITC Dynamic Gravity Dataset. It powers the International Trade Explorer (source).
Files
| File | Rows | Description |
|---|---|---|
ITPD_E_R2025_usd.parquet |
87,537,140 | One row per exporter × importer × industry × year, 1986–2023 (150 MB, zstd) |
web/ITPD_E_R2025_web.parquet |
33,468,219 | Smaller copy for the website (81 MB) — see below |
aggregates/world_region_flows.parquet |
166,242 | Cross-border trade by year × industry × exporter UN region × importer UN region, with trade-agreement and distance pieces (2.4 MB) |
aggregates/world_exporters.parquet |
985,102 | Cross-border exports by year × industry × exporting country (3.1 MB) |
lookups/country.csv |
257 | Country codes used in ITPD-E: ISO 3166-1 alpha-2/3/numeric, former ISO 3166-3 codes, UN M49 regions, LDC/LLDC/SIDS flags, World Bank region/income/lending (current) |
lookups/country_year.csv |
8,617 | ISO3 + year → ITPD-E/DGD dynamic code and the name used that year |
lookups/country_successor.csv |
36 | Former countries / aggregates → successor states (e.g. SVU → 15 states) |
lookups/industry.csv |
170 | ITPD-E industry id → description, broad sector |
lookups/flag_zero.csv |
3 | Meaning of flag_zero (p / r / u) |
lookups/wb_income_group.csv |
7,661 | World Bank income group by country and GNI year (1987–2023) |
lookups/dgd_country_year.csv |
8,151 | DGD 2.1 country attributes by year (WTO/GATT/EU membership, GDP, population, polity…), 1986–2019 |
lookups/dgd_pair_year.parquet |
1,956,949 | DGD 2.1 country-pair attributes by year (distance, contiguity, common language, colonial ties, trade agreements, sanctions), 1986–2019 |
Main table columns
exporter_iso3, exporter_iso3_dynamic, exporter_name, importer_iso3,
importer_iso3_dynamic, importer_name, broad_sector, industry_id,
industry_descr, year, trade, flag_mirror, flag_zero.
trade is in whole current US dollars (BIGINT). ITPD-E publishes millions of
USD; values were multiplied by 1,000,000 and rounded to the nearest dollar
(max change $0.50 per row; 99.5% of rows unchanged).
Web copy (web/ITPD_E_R2025_web.parquet)
The International Trade Explorer downloads this 81 MB file instead of the 150 MB full table. Same 13 columns, but:
- only rows with positive trade (zero-trade rows dropped: 54.1M rows flagged
u/r); traderounded to the nearest $1,000 (values under $1,000 kept exact, so no positive flow becomes zero);flag_mirror,exporter_nameandimporter_nameare left empty (uselookups/country.csv/country_year.csvfor names).
Row counts of positive flows are identical to the full table; the largest difference in any exporter × importer × year total is $14,172. Use the full table for research.
Aggregates (aggregates/)
Small pre-aggregated tables used by the explorer's world view, built from the full
table by scripts/build_aggregates.sql:
cross-border flows with positive trade, money rounded to the nearest $1,000 (values
under $1,000 kept exact). Agreement share = sum(pta_trade_usd) / sum(pta_known_trade_usd);
trade-weighted distance = sum(avg_distance_km × distance_known_trade_usd) / sum(distance_known_trade_usd).
Joins
- Country attributes:
exporter_iso3/importer_iso3→lookups/country.csv.iso3 - Income group in the trade year: (
iso3,year) →wb_income_group.csv(iso3,gni_year) - Gravity, country-year: (
exporter_iso3_dynamic,year) →dgd_country_year.csv(dynamic_code,year) - Gravity, pair-year: (
exporter_iso3_dynamic,importer_iso3_dynamic,year) →dgd_pair_year.parquet(dynamic_code_o,dynamic_code_d,year)
Caveats
- Domestic flows (exporter = importer) are included: production sold at home. They are complete only through 2021.
- Coverage: agriculture from 1986, manufacturing and mining & energy from 1988, services from 2000 (source changes in 2004 and 2010).
flag_mirrorranges 0–407 although documented as 0/1; > 0 means mirror data was used.- 11 country codes are not current ISO codes (7 former ISO 3166-3 codes;
SVU,BLX,ETF,FREare ITPD-E-specific).
Sources
- USITC ITPD-E R2025 — https://www.usitc.gov/data/gravity/itpde.htm
- USITC Dynamic Gravity Dataset 2.1 — https://www.usitc.gov/data/gravity/dgd.htm
- World Bank country classifications (OGHIST, CLASS) — https://datahelpdesk.worldbank.org/knowledgebase/articles/906519
- ISO 3166 / UN M49 codes via https://github.com/datasets/country-codes; ISO 3166-3 former codes compiled from Wikipedia
Please cite the original sources when using this data.
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