This visualization shows the Product Space, a network of how related different products are based on the mix of countries that export them. Nodes represent products (colored by industry), and edges represent how often products are co-exported by the same countries. The denser the connections, the easier it is for a country to move into producing that product.
Countries tend to move through this space over time, diversifying into nearby products. Some regions (like "electronics" or "machinery") are dense and well-connected, while others (like "petroleum" or "textiles") are more isolated. This helps explain why some countries grow faster than others.
Use the dropdown to highlight a country's current export basket, or search for a product to see its neighbors.
Sample data (first 5 products and edges): Products: 1. Paddy rice (Agriculture) - RCA: 1.2, Degree: 12 2. Maize (Agriculture) - RCA: 0.9, Degree: 8 3. Wheat (Agriculture) - RCA: 1.1, Degree: 10 4. Soybeans (Agriculture) - RCA: 0.8, Degree: 7 5. Coffee (Food) - RCA: 1.5, Degree: 5 Edges: 1. Paddy rice <-> Maize (Weight: 0.62) 2. Paddy rice <-> Wheat (Weight: 0.58) 3. Maize <-> Soybeans (Weight: 0.71) 4. Wheat <-> Soybeans (Weight: 0.45) 5. Coffee <-> Tea (Weight: 0.33)Why this dataset? It reveals the hidden structure of global trade and economic development. Unlike traditional datasets that focus on GDP or trade volumes, this shows the relationships between products, which helps explain why some countries diversify successfully while others get stuck. It's a beautiful example of how network science can illuminate real-world problems.