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What you should know about this indicator

  • This indicator shows which country was the largest source of imports for each country–year, based on import values in current US dollars.
  • In this data, imports are valued at "cost, insurance, and freight" (CIF). That is the value of the goods plus the cost of shipping and insuring them to the importing country's border. Not every country records its imports this way; for some of those that don't, the IMF adds an estimate of these costs.
  • The data covers goods only, not services such as software, tourism, or financial services.
  • The ten partners that are the largest source of imports for the most countries are shown by name. All other partners are grouped as "Other".
Top import partner category
IMF
For every country, the main trading partner supplying the largest share of its .
Source
International Monetary Fund (2026) – with major processing by Our World in Data
Last updated
October 5, 2026
Next expected update
October 2027
Date range
1948–2025

Sources and processing

This data is based on the following sources

International Monetary Fund – International Trade in Goods (by partner country) (IMTS)

The International Trade in Goods (by partner country) dataset, formerly called Direction of Trade Statistics (DOTS), shows the value of each country's exports and imports of goods, broken down by trading partner. It covers more than 200 countries and territories, with annual data from 1948 onward, in US dollars.

Most values come from the official trade statistics each country reports. For countries that report late, or don't publish their trade by partner, the IMF estimates the values from the data their trading partners report.

Retrieved on
October 5, 2026
Retrieved from
https://data.imf.org/en/datasets/IMF.STA:IMTS
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
International Monetary Fund. International Trade in Goods (by partner country), https://data.imf.org/en/datasets/IMF.STA:IMTS. Accessed on 05 October 2026.

The International Trade in Goods (by partner country) dataset, formerly called Direction of Trade Statistics (DOTS), shows the value of each country's exports and imports of goods, broken down by trading partner. It covers more than 200 countries and territories, with annual data from 1948 onward, in US dollars.

Most values come from the official trade statistics each country reports. For countries that report late, or don't publish their trade by partner, the IMF estimates the values from the data their trading partners report.

Retrieved on
October 5, 2026
Retrieved from
https://data.imf.org/en/datasets/IMF.STA:IMTS
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
International Monetary Fund. International Trade in Goods (by partner country), https://data.imf.org/en/datasets/IMF.STA:IMTS. Accessed on 05 October 2026.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator

For each country and year, we identified the partner country with the largest value of imports of goods. We then counted for how many countries each partner was ever the largest source of imports. The ten partners with the highest counts are shown individually, and all others are grouped as "Other".

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Top import partner category”, part of the following publication: Esteban Ortiz-Ospina, Bertha Rohenkohl, Veronika Samborska, Simon Van Teutem, Diana Beltekian, and Max Roser (2018) - “Trade and Globalization”. Data adapted from International Monetary Fund. Retrieved from https://archive.ourworldindata.org/20261023-101103/grapher/countrys-top-source-of-imported-goods.html [online resource] (archived on October 23, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

International Monetary Fund (2026) – with major processing by Our World in Data

Full citation

International Monetary Fund (2026) – with major processing by Our World in Data. “Top import partner category – IMF” [dataset]. International Monetary Fund, “International Trade in Goods (by partner country) (IMTS)” [original data]. Retrieved October 24, 2026 from https://archive.ourworldindata.org/20261023-101103/grapher/countrys-top-source-of-imported-goods.html (archived on October 23, 2026).

Download

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/countrys-top-source-of-imported-goods.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/countrys-top-source-of-imported-goods.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/countrys-top-source-of-imported-goods.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/countrys-top-source-of-imported-goods.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/countrys-top-source-of-imported-goods.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/countrys-top-source-of-imported-goods.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/countrys-top-source-of-imported-goods.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/countrys-top-source-of-imported-goods.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear