Datasets:
country_name stringclasses 1
value | country_iso3 stringclasses 1
value | partner_name stringclasses 204
values | partner_iso3 stringclasses 204
values | year int64 2.02k 2.02k | flow stringclasses 1
value | trade_value_usd float64 0.04 2.17B |
|---|---|---|---|---|---|---|
Dem. Rep. of the Congo | COD | Belgium | BEL | 2,015 | imports | 332,378,380.333 |
Dem. Rep. of the Congo | COD | Belgium | BEL | 2,015 | imports | 187,821,226.995 |
Dem. Rep. of the Congo | COD | India | IND | 2,015 | imports | 174,201,540.49 |
Dem. Rep. of the Congo | COD | France | FRA | 2,015 | imports | 295,419,947.249 |
Dem. Rep. of the Congo | COD | USA | USA | 2,015 | imports | 219,792,470.711 |
Dem. Rep. of the Congo | COD | Switzerland | CHE | 2,015 | imports | 195,203,241.836 |
Dem. Rep. of the Congo | COD | Norway | NOR | 2,015 | imports | 21,627,684.467 |
Dem. Rep. of the Congo | COD | Areas, nes | _X | 2,015 | imports | 3,015,579.671 |
Dem. Rep. of the Congo | COD | France | FRA | 2,015 | imports | 119,837,236.635 |
Dem. Rep. of the Congo | COD | France | FRA | 2,015 | imports | 90,949,071.984 |
Dem. Rep. of the Congo | COD | India | IND | 2,015 | imports | 474,667,830.697 |
Dem. Rep. of the Congo | COD | Areas, nes | _X | 2,015 | imports | 2,824,951.737 |
Dem. Rep. of the Congo | COD | USA | USA | 2,015 | imports | 703,514,462.611 |
Dem. Rep. of the Congo | COD | India | IND | 2,015 | imports | 239,773,796.94 |
Dem. Rep. of the Congo | COD | Switzerland | CHE | 2,015 | imports | 15,934,720.53 |
Dem. Rep. of the Congo | COD | Switzerland | CHE | 2,015 | imports | 7,760,035.756 |
Dem. Rep. of the Congo | COD | India | IND | 2,015 | imports | 43,307,710.403 |
Dem. Rep. of the Congo | COD | Other Asia, nes | S19 | 2,015 | imports | 4,417,084.049 |
Dem. Rep. of the Congo | COD | Other Asia, nes | S19 | 2,015 | imports | 14,708,557.088 |
Dem. Rep. of the Congo | COD | Norway | NOR | 2,015 | imports | 1,140,896.114 |
Dem. Rep. of the Congo | COD | USA | USA | 2,015 | imports | 78,888,677.098 |
Dem. Rep. of the Congo | COD | France | FRA | 2,015 | imports | 68,741,893.246 |
Dem. Rep. of the Congo | COD | Netherlands | NLD | 2,015 | imports | 138,233,246.8 |
Dem. Rep. of the Congo | COD | Australia | AUS | 2,015 | imports | 75,647,503.337 |
Dem. Rep. of the Congo | COD | United Kingdom | GBR | 2,015 | imports | 21,614,469.352 |
Dem. Rep. of the Congo | COD | Germany | DEU | 2,015 | imports | 81,383,222.782 |
Dem. Rep. of the Congo | COD | Rwanda | RWA | 2,015 | imports | 10,341,670.933 |
Dem. Rep. of the Congo | COD | Egypt | EGY | 2,015 | imports | 19,828,267.145 |
Dem. Rep. of the Congo | COD | Uganda | UGA | 2,015 | imports | 78,969,082.401 |
Dem. Rep. of the Congo | COD | United Arab Emirates | ARE | 2,015 | imports | 68,831,851.332 |
Dem. Rep. of the Congo | COD | South Africa | ZAF | 2,015 | imports | 1,483,699,120.637 |
Dem. Rep. of the Congo | COD | Australia | AUS | 2,015 | imports | 81,434,533.716 |
Dem. Rep. of the Congo | COD | United Kingdom | GBR | 2,015 | imports | 63,181,830.01 |
Dem. Rep. of the Congo | COD | Malaysia | MYS | 2,015 | imports | 5,839,652.998 |
Dem. Rep. of the Congo | COD | Canada | CAN | 2,015 | imports | 25,046,694.899 |
Dem. Rep. of the Congo | COD | South Africa | ZAF | 2,015 | imports | 1,708,161,119.48 |
Dem. Rep. of the Congo | COD | China | CHN | 2,015 | imports | 593,399,939.029 |
Dem. Rep. of the Congo | COD | United Rep. of Tanzania | TZA | 2,015 | imports | 117,318,809.286 |
Dem. Rep. of the Congo | COD | China | CHN | 2,015 | imports | 509,901,940.143 |
Dem. Rep. of the Congo | COD | Japan | JPN | 2,015 | imports | 141,449,617.441 |
Dem. Rep. of the Congo | COD | China | CHN | 2,015 | imports | 100,662,754.314 |
Dem. Rep. of the Congo | COD | Bulgaria | BGR | 2,015 | imports | 553,253.757 |
Dem. Rep. of the Congo | COD | United Arab Emirates | ARE | 2,015 | imports | 241,504,005.134 |
Dem. Rep. of the Congo | COD | Austria | AUT | 2,015 | imports | 1,361,827.115 |
Dem. Rep. of the Congo | COD | Belgium | BEL | 2,015 | imports | 51,787,590.522 |
Dem. Rep. of the Congo | COD | South Africa | ZAF | 2,015 | imports | 163,179,856.095 |
Dem. Rep. of the Congo | COD | Zambia | ZMB | 2,015 | imports | 348,799,664.308 |
Dem. Rep. of the Congo | COD | Austria | AUT | 2,015 | imports | 8,495,776.845 |
Dem. Rep. of the Congo | COD | Denmark | DNK | 2,015 | imports | 30,807,236.425 |
Dem. Rep. of the Congo | COD | Ukraine | UKR | 2,015 | imports | 1,046,123.565 |
Dem. Rep. of the Congo | COD | Finland | FIN | 2,015 | imports | 17,545,529.861 |
Dem. Rep. of the Congo | COD | Spain | ESP | 2,015 | imports | 60,868,554.575 |
Dem. Rep. of the Congo | COD | Finland | FIN | 2,015 | imports | 14,802,582.114 |
Dem. Rep. of the Congo | COD | Croatia | HRV | 2,015 | imports | 2,299,749.263 |
Dem. Rep. of the Congo | COD | Japan | JPN | 2,015 | imports | 56,511,184.593 |
Dem. Rep. of the Congo | COD | Singapore | SGP | 2,015 | imports | 5,827,192.634 |
Dem. Rep. of the Congo | COD | Croatia | HRV | 2,015 | imports | 2,344,124.121 |
Dem. Rep. of the Congo | COD | Lebanon | LBN | 2,015 | imports | 18,574,259.498 |
Dem. Rep. of the Congo | COD | China | CHN | 2,015 | imports | 1,250,068,130.738 |
Dem. Rep. of the Congo | COD | TΓΌrkiye | TUR | 2,015 | imports | 60,698,759.358 |
Dem. Rep. of the Congo | COD | Kenya | KEN | 2,015 | imports | 86,261,201.053 |
Dem. Rep. of the Congo | COD | Netherlands | NLD | 2,015 | imports | 46,670,536.996 |
Dem. Rep. of the Congo | COD | Italy | ITA | 2,015 | imports | 27,866,397.71 |
Dem. Rep. of the Congo | COD | Zambia | ZMB | 2,015 | imports | 355,620,972.198 |
Dem. Rep. of the Congo | COD | Bulgaria | BGR | 2,015 | imports | 394,791.124 |
Dem. Rep. of the Congo | COD | Canada | CAN | 2,015 | imports | 69,136,237.333 |
Dem. Rep. of the Congo | COD | Rep. of Korea | KOR | 2,015 | imports | 43,951,245.033 |
Dem. Rep. of the Congo | COD | United Kingdom | GBR | 2,015 | imports | 18,463,440.782 |
Dem. Rep. of the Congo | COD | Indonesia | IDN | 2,015 | imports | 37,013,626.404 |
Dem. Rep. of the Congo | COD | Viet Nam | VNM | 2,015 | imports | 12,363,139.765 |
Dem. Rep. of the Congo | COD | Belgium | BEL | 2,015 | imports | 79,426,575.802 |
Dem. Rep. of the Congo | COD | Malta | MLT | 2,015 | imports | 370,227.718 |
Dem. Rep. of the Congo | COD | TΓΌrkiye | TUR | 2,015 | imports | 75,799,165.205 |
Dem. Rep. of the Congo | COD | Rep. of Korea | KOR | 2,015 | imports | 33,050,913.178 |
Dem. Rep. of the Congo | COD | Ukraine | UKR | 2,015 | imports | 706,450.154 |
Dem. Rep. of the Congo | COD | Germany | DEU | 2,015 | imports | 231,087,392.481 |
Dem. Rep. of the Congo | COD | Lebanon | LBN | 2,015 | imports | 13,660,615.164 |
Dem. Rep. of the Congo | COD | Kenya | KEN | 2,015 | imports | 99,229,859.231 |
Dem. Rep. of the Congo | COD | Indonesia | IDN | 2,015 | imports | 28,304,788.226 |
Dem. Rep. of the Congo | COD | Germany | DEU | 2,015 | imports | 89,657,923.169 |
Dem. Rep. of the Congo | COD | Singapore | SGP | 2,015 | imports | 5,815,644.851 |
Dem. Rep. of the Congo | COD | Uganda | UGA | 2,015 | imports | 60,010,212.61 |
Dem. Rep. of the Congo | COD | Japan | JPN | 2,015 | imports | 74,336,199.926 |
Dem. Rep. of the Congo | COD | United Rep. of Tanzania | TZA | 2,015 | imports | 123,604,279.519 |
Dem. Rep. of the Congo | COD | Malaysia | MYS | 2,015 | imports | 16,367,525.089 |
Dem. Rep. of the Congo | COD | Singapore | SGP | 2,015 | imports | 26,976,047.289 |
Dem. Rep. of the Congo | COD | Germany | DEU | 2,015 | imports | 30,616,426.239 |
Dem. Rep. of the Congo | COD | Denmark | DNK | 2,015 | imports | 10,262,627.263 |
Dem. Rep. of the Congo | COD | Rwanda | RWA | 2,015 | imports | 10,140,567.937 |
Dem. Rep. of the Congo | COD | Egypt | EGY | 2,015 | imports | 19,039,874.767 |
Dem. Rep. of the Congo | COD | Portugal | PRT | 2,015 | imports | 6,414,095.268 |
Dem. Rep. of the Congo | COD | TΓΌrkiye | TUR | 2,015 | imports | 9,033,780.004 |
Dem. Rep. of the Congo | COD | United Arab Emirates | ARE | 2,015 | imports | 141,447,852.125 |
Dem. Rep. of the Congo | COD | Malta | MLT | 2,015 | imports | 789,587.882 |
Dem. Rep. of the Congo | COD | United Kingdom | GBR | 2,015 | imports | 107,686,399.294 |
Dem. Rep. of the Congo | COD | Viet Nam | VNM | 2,015 | imports | 11,129,940.265 |
Dem. Rep. of the Congo | COD | Italy | ITA | 2,015 | imports | 68,949,626.798 |
Dem. Rep. of the Congo | COD | Spain | ESP | 2,015 | imports | 32,961,091.939 |
Dem. Rep. of the Congo | COD | Portugal | PRT | 2,015 | imports | 5,255,382.409 |
Dem. Rep. of the Congo | COD | Indonesia | IDN | 2,015 | imports | 123,102.381 |
Dem. Rep. of the Congo β Imports by Trading Partner | Africa (UN Comtrade)
π 27,448 observations Β· 1 Africa countries Β· 2015β2023 Β· Repackaged by Electric Sheep Africa
TL;DR
This dataset contains 27,448 observations of International merchandise trade data across 1 Africa countries, spanning 2015β2023, covering 221 distinct indicators.
About the source
- Source: UN Comtrade
- Publisher: United Nations Statistics Division (UN Comtrade)
- License: other
- Topic: International merchandise trade
Geographic coverage
1 Africa countries Β· top rows shown below, sorted by row count:
| Country | Rows | First year | Last year |
|---|---|---|---|
Dem. Rep. of the Congo |
27,448 | 2015 | 2023 |
Indicators (sample)
Afghanistanβ AfghanistanAlbaniaβ AlbaniaAlgeriaβ AlgeriaAmerican Samoaβ American SamoaAndorraβ AndorraAngolaβ AngolaAnguillaβ AnguillaAntarcticaβ AntarcticaAntigua and Barbudaβ Antigua and BarbudaAreas, nesβ Areas, nes- ... and 211 more indicators
Schema
| Column | Type | Description | Example |
|---|---|---|---|
country_name |
string |
β | Dem. Rep. of the Congo |
country_iso3 |
string |
β | COD |
partner_name |
string |
β | Belgium |
partner_iso3 |
string |
β | BEL |
year |
int64 |
β | 2015 |
flow |
string |
β | imports |
trade_value_usd |
float64 |
β | 332378380.333 |
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-comtrade-dem-rep-of-the-congo-imports-by-partner")
df = ds["train"].to_pandas()
print(df.head())
Filter to one country
kenya = df[df["country_name"] == "KEN"]
Time-series for a single indicator
sample = (df[df["partner_name"] == "Belgium"]
.sort_values("year"))
sample.plot(x="year", y="trade_value_usd", title="Belgium")
Pivot to country Γ year matrix
matrix = (df[df["partner_name"] == "Belgium"]
.pivot_table(index="year", columns="country_name", values="trade_value_usd"))
print(matrix.tail())
Citation
@misc{africa_comtrade_dem_rep_of_the_congo_imports_by_partner_2023,
title = {Dem. Rep. of the Congo β Imports by Trading Partner | Africa (UN Comtrade)},
author = {United Nations Statistics Division (UN Comtrade)},
year = {2023},
url = {https://comtradeplus.un.org/},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-comtrade-dem-rep-of-the-congo-imports-by-partner}}
}
License
Released under other.
Original data Β© United Nations Statistics Division (UN Comtrade). When using this dataset, please cite both the original source above and the Electric Sheep Africa repackaging.
About Electric Sheep
Electric Sheep Africa is part of the Electric Sheep mission: a unified, ML-ready data layer for Africa on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.
Browse the full collection: huggingface.co/electricsheepafrica
Provenance: ingested 2026-06-17 via the Electric Sheep pipeline. Source URL: https://comtradeplus.un.org/
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